Data Science Course with Python in Kolkata, India

Get hands-on Python skills and accelerate your data science career

  • Get 42 hours of live and interactive instructor led training
  • Interactive Statistical Learning with advanced Excel
  • Learn Advanced Statistics and Predictive Modeling with Python 
  • 220,000 + Professionals Trained
  • 250 + Workshops every month
  • 100 + Countries and counting

Grow your Data Science skills

Understand and learn the fundamentals of Data Science with KnowledgeHut’s Data Science with Python Course. Start from the basics and get to an advanced level in a span of weeks. Get active programming experience in Python that could immediately be applied to real-world projects. Equip yourself with the skills you need to be a skilled data scientist.

..... Read more
Read less


  • 42 Hours of Live Instructor-Led Sessions

  • 60 Hours of Assignments and MCQs

  • 36 Hours of Hands-On Practice

  • 6 Real-World Live Projects

  • Fundamentals to an Advanced Level

  • Code Reviews by Professionals

Why get the Data Science with Python certification in kolkata


Data Science has bagged the top spot in LinkedIn’s Emerging Jobs Report for the last three years. Various companies around the world are looking for professionals who can transform data into strategic plans for their organizations. Acquire in-demand data science and Python skills to enable more data driven decisions.

..... Read more
Read less

Not sure how to get started? Let our Learning Advisor help you.

Contact Learning Advisor

The KnowledgeHut Edge

Learn by Doing

Our immersive learning approach lets you learn by doing and acquire immediately applicable skills hands-on.

Real-World Focus

Learn theory backed by real-world practical case studies and exercises. Skill up and get productive from the get-go.

Industry Experts

Get trained by leading practitioners who share best practices from their experience across industries.

Curriculum Designed by the Best

Our Data Science advisory board regularly curates best practices to emphasize real-world relevance.

Continual Learning Support

Webinars, e-books, tutorials, articles, and interview questions - we're right by you in your learning journey!

Exclusive Post-Training Sessions

Six months of post-training mentor guidance to overcome challenges in your Data Science career.


Prerequisites for the Data Science with Python training program

  • There are no prerequisites to attend this course in Kolkata. 
  • Elementary programming knowledge will be of advantage. 

Who should attend the Data Science with Python course?

Professionals in the field of data science

Professionals looking for a robust, structured Python learning program

Professionals working with large datasets

Software or data engineers interested in quantitative analysis

Data analysts, economists, researchers

Data Science with Python Course Schedules for Kolkata

100% Money Back Guarantee

Can't find the batch you're looking for?

Request a Batch

What you will learn in the Data Science with Python course

Python Distribution

Anaconda, basic data types, strings, regular expressions, data structures, loops, and control statements.

User-defined functions in Python

Lambda function and the object-oriented way of writing classes and objects.

Datasets and manipulation

Importing datasets into Python, writing outputs and data analysis using Pandas library.

Probability and Statistics

Data values, data distribution, conditional probability, and hypothesis testing.

Advanced Statistics

Analysis of variance, linear regression, model building, dimensionality reduction techniques.

Predictive Modelling

Evaluation of model parameters, model performance, and classification problems.

Time Series Forecasting

Time Series data, its components and tools.

Skill you will gain with the Data Science with Python course

Python programming skills

Manipulating and analysing data using Pandas library

Data visualization with Matplotlib, Seaborn, ggplot

Data distribution: variance, standard deviation, more

Calculating conditional probability via hypothesis testing

Analysis of Variance (ANOVA)

Building linear regression models

Using Dimensionality Reduction Technique

Building Binomial Logistic Regression models

Building KNN algorithm models to find the optimum value of K

Building Decision Tree models for regression and classification

Visualizing Time Series data and components

Exponential smoothing

Evaluating model parameters

Measuring performance metrics

Transform Your Workforce

Harness the power of data to unlock business value

Invest in forward-thinking data talent to leverage data’s predictive power, craft smart business strategies, and drive informed decision-making.

  • Immersive Learning with a Learn-by-Doing approach.
  • Applied Learning to get your teams project-ready.
  • Align skill development to your most important objectives.
  • Get in touch for customized corporate training programs.

500+ Clients

Data Science with Python Course Curriculum

Download Curriculum

Learning objectives
Understand the basics of Data Science and gauge the current landscape and opportunities. Get acquainted with various analysis and visualization tools used in data science.


  • What is Data Science?
  • Data Analytics Landscape
  • Life Cycle of a Data Science Project
  • Data Science Tools and Technologies 

Learning objectives
The Python module will equip you with a wide range of Python skills. You will learn to:

  • To Install Python Distribution - Anaconda, basic data types, strings, and regular expressions, data structures and loops, and control statements that are used in Python
  • To write user-defined functions in Python
  • About Lambda function and the object-oriented way of writing classes and objects 
  • How to import datasets into Python
  • How to write output into files from Python, manipulate and analyse data using Pandas library
  • Use Python libraries like Matplotlib, Seaborn, and ggplot for data visualization


  • Python Basics
  • Data Structures in Python 
  • Control and Loop Statements in Python
  • Functions and Classes in Python
  • Working with Data
  • Data Analysis using Pandas
  • Data Visualisation
  • Case Study


  • How to install Python distribution such as Anaconda and other libraries
  • To write python code for defining as well as executing your own functions
  • The object-oriented way of writing classes and objects
  • How to write python code to import dataset into python notebook
  • How to write Python code to implement Data Manipulation, Preparation, and Exploratory Data Analysis in a dataset

Learning objectives
In the Probability and Statistics module you will learn:

  • Basics of data-driven values - mean, median, and mode
  • Distribution of data in terms of variance, standard deviation, interquartile range
  • Basic summaries of data and measures and simple graphical analysis
  • Basics of probability with real-time examples
  • Marginal probability, and its crucial role in data science
  • Bayes’ theorem and how to use it to calculate conditional probability via Hypothesis Testing
  • Alternate and Null hypothesis - Type1 error, Type2 error, Statistical Power, and p-value


  • Measures of Central Tendency
  • Measures of Dispersion 
  • Descriptive Statistics 
  • Probability Basics
  • Marginal Probability
  • Bayes Theorem
  • Probability Distributions
  • Hypothesis Testing


  • How to write Python code to formulate Hypothesis
  • How to perform Hypothesis Testing on an existent production plant scenario

Learning objectives
Explore the various approaches to predictive modelling and dive deep into advanced statistics:

  • Analysis of Variance (ANOVA) and its practicality
  • Linear Regression with Ordinary Least Square Estimate to predict a continuous variable
  • Model building, evaluating model parameters, and measuring performance metrics on Test and Validation set
  • How to enhance model performance by means of various steps via processes such as feature engineering, and regularisation
  • Linear Regression through a real-life case study
  • Dimensionality Reduction Technique with Principal Component Analysis and Factor Analysis
  • Various techniques to find the optimum number of components or factors using screen plot and one-eigenvalue criterion, in addition to a real-Life case study with PCA and FA.


  • Analysis of Variance (ANOVA)
  • Linear Regression (OLS)
  • Case Study: Linear Regression
  • Principal Component Analysis
  • Factor Analysis
  • Case Study: PCA/FA


  • With attributes describing various aspect of residential homes for which you are required to build a regression model to predict the property prices
  • Reducing Dimensionality of a House Attribute Dataset to achieve more insights and better modelling

Learning objectives
Take your advanced statistics and predictive modelling skills to the next level in this advanced module covering:

  • Binomial Logistic Regression for Binomial Classification Problems
  • Evaluation of model parameters
  • Model performance using various metrics like sensitivity, specificity, precision, recall, ROC Curve, AUC, KS-Statistics, and Kappa Value
  • Binomial Logistic Regression with a real-life case Study
  • KNN Algorithm for Classification Problem and techniques that are used to find the optimum value for K
  • KNN through a real-life case study
  • Decision Trees - for both regression and classification problem
  • Entropy, Information Gain, Standard Deviation reduction, Gini Index, and CHAID
  • Using Decision Tree with real-life Case Study


  • Logistic Regression
  • Case Study: Logistic Regression
  • K-Nearest Neighbour Algorithm
  • Case Study: K-Nearest Neighbour Algorithm
  • Decision Tree
  • Case Study: Decision Tree


  • Building a classification model to predict which customer is likely to default a credit card payment next month, based on various customer attributes describing customer characteristics
  • Predicting if a patient is likely to get any chronic kidney disease depending on the health metrics
  • Building a model to predict the Wine Quality using Decision Tree based on the ingredients’ composition

Learning objectives
All you need to know to work with time series data with practical case studies and hands-on exercises. You will:

  • Understand Time Series Data and its components - Level Data, Trend Data, and Seasonal Data
  • Work on a real-life Case Study with ARIMA.


  • Understand Time Series Data
  • Visualizing Time Series Components
  • Exponential Smoothing
  • Holt's Model
  • Holt-Winter's Model
  • Case Study: Time Series Modelling on Stock Price


  • Writing python code to Understand Time Series Data and its components like Level Data, Trend Data and Seasonal Data.
  • Writing python code to Use Holt's model when your data has Constant Data, Trend Data and Seasonal Data. How to select the right smoothing constants.
  • Writing Python code to Use Auto Regressive Integrated Moving Average Model for building Time Series Model
  • Use ARIMA to predict the stock prices based on the dataset including features such as symbol, date, close, adjusted closing, and volume of a stock.

Learning objectives
This industry-relevant capstone project under the experienced guidance of an industry expert is the cornerstone of this Data Science with Python course. In this immersive learning mentor-guided live group project, you will go about executing the data science project as you would any business problem in the real-world.


  • Project to be selected by candidates.

FAQs on Data Science with Python Course in kolkata

Data Science with Python Training

The Data Science with Python course has been thoughtfully designed to make you a dependable Data Scientist ready to take on significant roles in top tech companies. At the end of the course, you will be able to:

  • Build Python programs: distribution, user-defined functions, importing datasets and more
  • Manipulate and analyse data using Pandas library
  • Data visualization with Python libraries: Matplotlib, Seaborn, and ggplot
  • Distribution of data: variance, standard deviation, interquartile range
  • Calculating conditional probability via Hypothesis Testing
  • Analysis of Variance (ANOVA)
  • Building linear regression models, evaluating model parameters, and measuring performance metrics
  • Using Dimensionality Reduction Technique
  • Building Binomial Logistic Regression models, evaluating model parameters, and measuring performance metrics
  • Building KNN algorithm models to find the optimum value of K
  • Building Decision Tree models for both regression and classification problems
  • Build Python programs: distribution, user-defined functions, importing datasets and more
  • Manipulate and analyse data using Pandas library
  • Visualize data with Python libraries: Matplotlib, Seaborn, and ggplot
  • Build data distribution models: variance, standard deviation, interquartile range
  • Calculate conditional probability via Hypothesis Testing
  • Perform analysis of variance (ANOVA)
  • Build linear regression models, evaluate model parameters, and measure performance metrics
  • Use Dimensionality Reduction
  • Build Logistic Regression models, evaluate model parameters, and measure performance metrics
  • Perform K-means Clustering and Hierarchical Clustering
  • Build KNN algorithm models to find the optimum value of K
  • Build Decision Tree models for both regression and classification problems
  • Build data visualization models for Time Series data and components
  • Perform exponential smoothing

The program is designed to suit all levels of Data Science expertise. From the fundamentals to the advanced concepts in Data Science, the course covers everything you need to know, whether you’re a novice or an expert. To facilitate development of immediately applicable skills, the training adopts an applied learning approach with instructor-led training, hands-on exercises, projects, and activities.

Yes, our Data Science with Python course is designed to offer flexibility for you to upskill as per your convenience. We have both weekday and weekend batches to accommodate your current job.

In addition to the training hours, we recommend spending about 2 hours every day, for the duration of course.

The Data Science with Python course is ideal for:

  • Anyone Interested in the field of data science
  • Anyone looking for a more robust, structured Python learning program
  • Anyone looking to use Python for effective analysis of large datasets
  • Software or Data Engineers interested in quantitative analysis with Python
  • Data Analysts, Economists or Researcher

There are no prerequisites for attending this course, however prior knowledge of elementary programming, preferably using Python, would prove to be handy.

To attend the Data Science with Python training program, the basic hardware and software requirements are as mentioned below -

Hardware requirements

  • Windows 8 / Windows 10 OS, MAC OS >=10, Ubuntu >= 16 or latest version of other popular Linux flavors
  • 4 GB RAM
  • 10 GB of free space

Software Requirements

  • Web browser such as Google Chrome, Microsoft Edge, or Firefox

System Requirements

  • 32 or 64-bit Operating System
  • 8 GB of RAM

On adequately completing all aspects of the Data Science with Python course, you will be offered a course completion certificate from KnowledgeHut.

In addition, you will get to showcase your newly acquired data-handling and programming skills by working on live projects, thus, adding value to your portfolio. The assignments and module-level projects further enrich your learning experience. You also get the opportunity to practice your new knowledge and skillset on independent capstone projects.

By the end of the course, you will have the opportunity to work on a capstone project. The project is based on real-life scenarios and carried-out under the guidance of industry experts. You will go about it the same way you would execute a data science project in the real business world.

Data Science with Python Workshop

The Data Science with Python workshop at KnowledgeHut is delivered through PRISM, our immersive learning experience platform, via live and interactive instructor-led training sessions.

Listen, learn, ask questions, and get all your doubts clarified from your instructor, who is an experienced Data Science and Machine Learning industry expert.

The Data Science with Python course is delivered by leading practitioners who bring trending, best practices, and case studies from their experience to the live, interactive training sessions. The instructors are industry-recognized experts with over 10 years of experience in Data Science. 

The instructors will not only impart conceptual knowledge but end-to-end mentorship too, with hands-on guidance on the real-world projects.

Our Date Science course focuses on engaging interaction. Most class time is dedicated to fun hands-on exercises, lively discussions, case studies and team collaboration, all facilitated by an instructor who is an industry expert. The focus is on developing immediately applicable skills to real-world problems.

Such a workshop structure enables us to deliver an applied learning experience. This reputable workshop structure has worked well with thousands of engineers, whom we have helped upskill, over the years. 

Our Data Science with Python workshops are currently held online. So, anyone with a stable internet, from anywhere across the world, can access the course and benefit from it.

Schedules for our upcoming workshops in Data Science with Python can be found here.

We currently use the Zoom platform for video conferencing. We will also be adding more integrations with Webex and Microsoft Teams. However, all the sessions and recordings will be available right from within our learning platform. Learners will not have to wait for any notifications or links or install any additional software.

You will receive a registration link from PRISM to your e-mail id. You will have to visit the link and set your password. After which, you can log in to our Immersive Learning Experience platform and start your educational journey.

Yes, there are other participants who actively participate in the class. They remotely attend online training from office, home, or any place of their choosing.

In case of any queries, our support team is available to you 24/7 via the Help and Support section on PRISM. You can also reach out to your workshop manager via group messenger.

If you miss a class, you can access the class recordings from PRISM at any time. At the beginning of every session, there will be a 10-12-minute recapitulation of the previous class.

Should you have any more questions, please raise a ticket or email us at and we will be happy to get back to you.

Data Science with Python

What is Data Science?

Data science is a fairly new and upcoming field of study which deals with- you guessed it- data. In this day and age, data has become the be all and end all of pretty much every industry. It has revolutionized the way business is conducted, both online and offline, making data science the most sought-after career choice for anyone with an IT background. It offers you scope for research, is an exciting and challenging job and provides a sense of accomplishment as well as you can see exactly how you are affecting the market trends with your work.  

Kolkata is one of the major and historic cities in India. With time, it has grown to be one of the most technologically advanced cities. It is home to some of the best institutions in the country which deal with data science and also has some of the leading companies such as IBM, Square1, Top Gear,  ERM, ERev Max Technologies, PwC, Maven Workforce, BridgeTree etc.

Data science involves collecting, arranging and examining data to figure out unique patterns and solutions for a variety of problems. From politics to healthcare to e-commerce- everyone wants a piece of this revolutionary career. So, there is no dearth of opportunities. And the fact that data scientists make good money is an added advantage that encourages people to join this sector. Other reasons why data science is so popular are: 

  • Because it allows you to explore more than just coding and databases
  • Because data scientists are very much in demand by the big shots of the industry.

Becoming a data scientist is a daunting task, one that involves a good mix of technical and practical skills. Indian Institute of Management Calcutta, Ivy Professional School, S.N. Bose National Centre For Basic Sciences, DBA: Best Data Science, Python, Machine Learning, Data Analytics, AI Certification Course & Training, Praxis Business School, Purba Kolkata Polytechnic For Computer Science,  are some of the best institutes which offer Data science courses. This is what makes living in Kolkata such an advantage for the data scientists.

While you need to be academically brilliant (most data science people are Ph.D. holders or at least postgraduates), business skills and creativity are also a mandatory requirement that you cannot avoid. Here are some technical skills that every company looks for in a data scientist, master these skills and you are sure to be in demand! 

  • Python coding: Python is a simple and well-known platform among software engineers and data analysts where you can develop data sets, store information and explore the different permutations and combinations of the said data to develop advanced algorithms. 
  • R Programming: R Programming is a more advanced tool used by data scientists to analyze given data and gather valuable insights. The platform also allows you to sort and arrange unstructured data into logical compartments and categories. It is a flexible, versatile and hassle-free problem-solving tool preferred by established data scientists and professionals. 
  • SQL Database: SQL is perhaps one of the most extensive database systems in the market which enables users to create logical data sets, get in-depth insights and connect with other programs as well. You can also tweak the basic structure and core code of the data set and customize it to your liking.  
  • Hadoop: Most companies do not require Hadoop, however a basic knowledge of how this platform works can get you some brownie points from your employer. It allows the user to design separate data sets, optimize it to the requirement, sort through unstructured data and create accurate algorithms.   
  • Apache Spark: Apache Spark is a popular data sharing tool that comes with intuitive and advanced data computational technology. The robust interface is faster than Hadoop, offers better features and is easier to work with. Plus, you get cloud support.  
  • Machine Learning: Machine Learning and AI are other necessary skills every aspiring data scientist must learn. With coding and programming, one can control every aspect of the data, from how it is arranged to how it is presented to people. AI allows you to create advanced systems which only enhance the effectiveness and precision of the program.  
  • Data Visualization: Data visualization tools like d3.js, ggplot, and Tableau enables users to create data sets, arrange data and customize it. Here, you can convert data sets into multiple formats, gather insights and yield optimized results easily as well.  

Working in the data science sector is not just about mastering the technical skills and becoming a pro at coding. There are certain behavioral traits that employers expect from a data scientist. Possessing these traits gives one an edge over the others in the industry. These are:

  1. Thirst for knowledge 
  2. Passion for learning 
  3. An open mind 
  4. Creative and innovative thinking 
  5. Quick problem solving skills 
  6. Patience and perseverance 

Being a data scientist is a once in a lifetime opportunity that you just have to make the best out of. It gives you the experience and exposure into the intricate details of how market trends are formed and manipulated. Kolkata is a city which offers some lucrative packages and opportunities to data scientist as it is home to some of the most prominent organizations such as IBM, Square1, Top Gear,  ERM, ERev Max Technologies, PwC, Maven Workforce, BridgeTree etc. Here are some perks of being a data scientist which you should know about; 

  • Salary: Data scientists get paid well, and this is among the highest paying jobs in the world according to Glassdoor. And the fact that there is no shortage of jobs in the IT industry for data scientists makes this a rewarding vocation. 
  • The Prestige: Data scientists are highly appreciated in the IT area. They typically hold impressive degrees and PhDs for their research work and are thus considered to be obviously brainy and bright. 
  • Job Satisfaction: Being a data scientist is a very sustaining and thrilling career opportunity. It doesn’t confine you to your work desk all day like other software engineers. As a data scientist, your job would involve going to the sites, traveling around the world and joining meetings as well.  
  • Scope for Growth: Data science as a field is still evolving and hence has room for research and expansion. One can work together with associated data scientists and work out new and ground-breaking ways to shape data sets, get better insights and new systematic standpoints. 

Data Scientist Skills & Qualifications

Of course, as a data scientist your job will not be limited to the office space but also involve interacting with clients, as you will be required to market your product and understand the latest trends which govern the said market. Here are some business skills that companies look for in budding data scientists and graduates; 

  • Decision-making Skills: this involves setting up harmonious relations with other branches, organizing meetings, and handling tons of other things, as a data researcher one has to be good at multitasking. 
  • Mechanical Skills: practical skills are vital to your profession as a successful data scientist. One has to be experienced in software design platforms like Hadoop and Spark and have a decent knowledge about the cutting-edge measures taken up by AI to advance data science.  
  • Communication Skills: you will have to contact investors, clients, project heads and sometimes even the customers as part of your job to get the overall mood of the market. A pleasant personality, great vocabulary and a passion for your field is mandatory 
  • Razor Sharp Intellect: business acumen and technical wit are perhaps the most important and rudimentary requirements of the job. You should be able to come up with actionable solutions, tackle complicated solutions, find unique patterns and handle almost every situation with a sense of calm and maturity.  
  • Industry Knowledge: lastly the data scientist must have exhaustive information about the different aspects which directly or indirectly affect the industry. This doesn’t just provide valuable insights about the market but also allows marketers to gain the faith of the clients in return. 

Data science is an ever growing field, and anyone who wants to succeed in this sector must be updated with the latest trends and technologies of the industry. Here are some simple and effective ways in which one can brush up on their skills in data science;   

  • Boot camps: Data Science bootcamps in Kolkata provide short term courses in programming languages like Python. The camp lasts for about 4 to 5 days and provides a basic understanding of the coding. 
  • MOOC courses: MOOCs are conducted online courses and are suitable for professionals who want to familiarise themselves with the latest industry trends. The classes are taught by data science experts, and enable students to get a better in depth understanding of the subject. 
  • Certifications: Certificate courses are a great addition for your CV. It enhances your market value and makes one eligible to better paying jobs in the industry. Here are some of the data science certifications that you can go for:
    • Cloudera Certified Associate - Data Analyst
    • Cloudera Certified Professional: CCP Data Engineer
    • Applied AI with Deep Learning, IBM Watson IoT Data Science Certificate
  • Projects: Projects allow data science candidates to improve their problem solving skills and develop a unique perspective.  
  • Competitions: Competitions like Kaggle connect you with other data scientists in the industry and widen your network. 

Kolkata has a thriving and ever growing IT sector which requires talented and learned data scientists who can come up with new and innovative solutions to complex problems. There are various leading companies headquartered in and around Kolkata, such as TCS, Tech Mahindra, HCL, Wipro, etc. Data scientists are in demand in other sectors as well. There are banks, hospitals, corporate firms, and other organisations where data scientists, analysts and software engineers are in hot demand. 

Data science is more practical than theory. You have to always work on your technical skills, work on extensive lines of code and learn about the latest developments in the sector. The best way to improve your data science skills is to keep writing new algorithm and executing them. Here, we have categorized different problems according to their difficulty level and your expertise level:

  • Beginner Level
    • Iris Data Set: this is among the easiest, simplest and most preferred data sets for amateurs. The set is used for recognising patterns, incorporating multiple codes and applying them to real-life situations. This dataset has just 4 rows and 50 columns. Practice Problem: The problem is using these parameters to predict the class of the flowers. 
  • Loan Prediction Data Set: this is an extensive and complex data set that allows the user to collect and analyse huge data volumes. The platform is used in the banking sector. While working with this dataset, the user is expected to have a detailed understanding of banking and insurance It is a classification problem dataset with 13 columns and 615 rows. Practice Problem: The problem is to predict if the loan will be approved or not. 
    • Bigmart Sales Data Set: this data set deals with the retail sector. Data Science and Business Analytics are combined to calculate interest, keep track of inventory manage and customize product bundling, etc. This dataset is a regression problem with 12 columns and 8523 rows. Practice Problem: The problem is predicting the sales of the retail store. 
  • Intermediate Level:
    • Black Friday Data Set: this dataset is created from the retail sector. With this dataset, you will be able to analyse the shopping patterns, tastes and preferences of customers. It is a regression problem with 12 columns and 550,069 rows. Practice Problem: The problem is predicting the total amount of purchase.
  • Human Activity Recognition Data Set: This dataset takes the trends of smartphones collected via inertial sensors. It is comprised of 30 participants. The dataset consists of 561 columns and 10,299 rows.
    Practice Problem: The problem is the prediction of the category of human activity. 

    • Text Mining Data Set: the text mining data set consists of aviation safety reports, stating the problems passengers faced. The data set incorporates 30,438 rows and 21,519 columns.
      Practice Problem: The problem is the classification of documents based on their labels. 
  • Advanced Level:
    • Urban Sound Classification: It is an advanced, high level data set which collects and implements machine learning concepts to real-life problems. It includes 10 classes with 8,732 audio files of urban sounds,
      Practice Problem: The problem is the classification of the sound obtained from specific audio. 
    • Identify the digits data set: Consisting of 7000 images of 31 MB and 28X28 dimensions, this data set allows you in an in depth view into how the image is created and visible online.
      Practice Problem: The problem is identifying the digits present in an image. 
    • Vox Celebrity Data Set: This dataset is used for identifying speakers on a large scale. It uses YouTube videos to take out the words spoken by celebrities.It contains 100,000 words spoken by 1,251 celebrities.
      Practice Problem: The problem is the identification of the voice of a celebrity.

How to Become a Data Scientist in Kolkata, India

Want to become a data scientist in Kolkata? Here is what you should do:

  • Select the right programming language, we would recommend R and Python. 
  • Brush on your math and stats skills, data science requires a thorough understanding of these subjects
  • Work on data visualisation as well, data visualisation is basically how one presents the content and establishes contact with the end user. 
  • Learn the fundamental concepts of AI and  ML as well as these often come in handy. 

Learning data science is no piece of cake, it involves a lot of studying and practice. Here’s how you can do it:

  • Get the required academic degree and complete the necessary degree courses with proper certificates. 
  • Understanding the intricate concepts of data science, especially unstructured data 
  • Master the coding platforms and programming languages for creating data sets and analysing data 
  • Learn about AI and ML concepts 
  • Know about data visualisation tools like ggplot 
  • A degree is necessary for students to broaden their network and know about fellow data scientists and coders in the industry.   
  • It allows one to learn in a systematic and rational manner
  • The institution that offers the degree can be a great addition to the CV and add on to one's industry value. 
  • It offers students great internship opportunities.

With a masters degree in data science, one will be better equipped to deal with the complications of the industry. An advanced understanding of the data sets and coding boosts a data scientist’s confidence and demand in considerable amounts.  If you are having trouble in deciding whether you should go for a Master’s degree, you can try grading yourself on the basis of the below scorecard. If your score is more than 6 points, you should get a Master’s degree:

  • A strong STEM (Science/Technology/Engineering/Management) background: 0 point
  • A weak STEM background (biochemistry/biology/economics or another similar degree/diploma): 2 points
  • A non-STEM background: 5 points
  • Less than 1 year of experience in Python: 3 points
  • No experience of a job that requires regular coding: 3 points
  • Independent learning is not your cup of tea: 4 points
  • Cannot understand that this scorecard is a regression algorithm: 1 point

Coding enhances your chances of getting a better paying job in the industry:

  • Programming is necessary for understanding data sets 
  • It is required for dealing with big stats
  • Programming platforms offer the perfect framework for candidates to develop data sets. 

Data Scientist Salary in Kolkata, India

In Kolkata, the average annual salary of a data scientist is Rs. 7,50,000 .

A Data Scientist earns an average of about Rs. 7,50,000 per year in Kolkata as opposed to Rs. 6,15,496 in Bangalore.

Kolkata offers an annual salary of Rs. 7,50,000 per year as compared to Rs. 9,92,129 offered in Delhi.

As opposed to the Data scientist’s average annual salary of Rs. 7,50,000 in Kolkata, data scientists in Mumbai make about Rs. 6,72,492  annually.

The average annual salary of a data scientist in Kolkata is Rs. 7,50,000.  As of now, Kolkata is the only city in West Bengal for which the average salary data is available.

As so many new firms have entered the market in the data science field in Kolkata, the demand for data scientists have also increased. Also, with the BPO expansion, there is a requirement for entry level as well as mid-management professionals. 

The benefits of being a data scientist in Kolkata is that it offers multiple job opportunities, job growth, affordable living, and gives a pay that is up to the mark.

The advantage of being a data Scientist in Kolkata is that there are so many new opportunities in Kolkata. Many small and mid-sized firms have started to realize the power of Data Science and are now looking for data scientists. Data Scientists have the luxury to choose any field that interests them. Also, there is a shift from traditional analytics role to emerging analytics deliverables that offers new horizontals and verticals to your area of interest. They also gain the attention of upper level management as they provide useful insights that help in making important business decisions. 

The companies hiring Data Scientists in Kolkata are Spaa Data Private Ltd, Capgemini. Trapper Technology, Agnik, ICRA Online Limited, TCG Lifesciences, Ps Group, etc.

Data Science Conference in Kolkata, India

S.NoConference nameDateVenue
1.CM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD), Kolkata, India3-5 January, 2019

City Centre New Town, Action Area 2 D, Plot No.11/5, New Rajarhat, Kolkata 700157, India

2.7th International Data Science Summit, Kolkata, India20 September, 2019Biswa Bangla Convention Centre Newtown, Kolkata
3.AIMinds Kolkata, India11 May, 2019NSHM Knowledge Campus, 124(60), Basanta Lal Saha Rd, Tara Park, Behala, Kolkata, West Bengal – 700053
4.Advanced Programme in Data Sciences (APDS), Kolkata, India

IIM Calcutta, Diamond Harbour Rd, Joka, Kolkata, West Bengal 700104
5.FIRE 2019: 11th meeting of the Forum for Information Retrieval Evaluation
Dec 12, 2019 - Dec 15, 2019
Indian Statistical Institute, Plot No. 203, Barrackpore Trunk Road, Baranagar, Kolkata, West Bengal 700108

1. ACM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD), Kolkata

  • About the conference: The conference is hosted by Division II of Computer Society of India and covers the topics of big data, machine learning, and data analytics.
  • Event Date: 3-5 January, 2019
  • Venue: City Centre New Town, Action Area 2 D, Plot No.11/5, New Town Rajarhat, Kolkata 700157, India
  • Days of Program: 3
  • Timings: 8:30 A.M. to 8 P.M.
  • Purpose: The conference aims at enhancing the knowledge in data analytics by holding sessions by data science experts on topics such as Deep Learning, medical image retrieval, Perception Ranking, Deeply Coupled Graph Structure and similar topics related to data analytics, and also invites research papers on Data Science, its application and Databases.
  • How many speakers: 4
  • Speakers & Profile:
    • Milind Tambe, Helen N. and Emmett H. Jones Professor in Engineering; Professor, Computer Science & Industrial and Systems Engineering Departments, University of Southern California
    • Subbarao Kambhampati, Professor, Dept. of Computer Science & Engg., Fulton School of Engineering, Arizona State University, Tempe Arizona
    • Raymond J. Mooney, Professor, Professor of Computer Science, The University of Texas at Austin; Director of the UT AI Laboratory
    • Krishna P. Gummadi, Faculty, Head, Networked Systems Research Group, Max Planck Institute for Software Systems (MPI-SWS)
  • Registration cost:
    • Early Bird Up to Dec 10, 2018
      • Professional (Member of CSI/ACM): INR 11800
      • Professional (Non-Member): INR 16000
      • Academician (Member of CSI/ACM): INR 6000
      • Academician (Non-member): INR 7700
      • Student (Member of CSI/ACM): INR 3550
      • Student (Non-member): INR 5000
    • After Dec 10, 2018
      • Professional (Member of CSI/ACM): INR 13570
      • Professional (Non-Member): INR 18400
      • Academician (Member of CSI/ACM): INR 6900
      • Academician (Non-member): INR 8800
      • Student (Member of CSI/ACM): INR 4100
      • Student (Non-member): INR 5750

  • Who are the major sponsors:
    • American Express
    • Tata Consultancy Services
    • Microsoft
    • Adobe
    • IBM
    • Google
    • Rakuten
    • Intel
    • Hike
    • Amazon

2. 7th International Data Science Summit, Kolkata

  • About the conference: The conference is organized by the Data Science Foundation and brings together practitioners and contributors in data science to share their innovative ideas to efficiently understand the various aspects of Data Science.
  • Event Date: 20 September, 2019
  • Venue: Biswa Bangla Convention Centre NewTown, Kolkata
  • Days of Program: 1
  • Purpose: The conference aims to provide its attendees a better idea of the new products introduced in IoT, Visualization, AI, and Analytics, and discuss and understand the algorithms applied in data science.
  • Whom can you Network with in this Conference:
    • Students
    • Research / Academia
    • Corporates
  • Who are the major sponsors:
    • Google Developers
    • Business Brio
    • Webel
    • DBA
    • STPI
    • Somnetics
    • Times Internet
    • Ideal analytics
    • RailTel
    • MSTC
    • Indian Oil
    • Ola
    • Protiviti
    • TCG Digital
    • IDCO
    • CESC Limited
    • Var India

    3. AIMinds Kolkata

    • About the conference: It is a meetup which is organized in collaboration with NSHM Knowledge Campus to enrich the minds of data enthusiasts by providing them an opportunity to share knowledge and questions with the researchers and practitioners in AI and Data Science.
    • Event Date: 11 May, 2019
    • Venue: NSHM Knowledge Campus, 124(60), Basanta Lal Saha Rd, Tara Park, Behala, Kolkata, West Bengal – 700053
    • Days of Program: 1
    • Timings: 10:00 AM to 1:00 PM
    • Purpose: It is a meetup which is aimed at sharing knowledge among aspiring minds and enthusiasts in Analytics, Data Science and AI.
    • How many speakers: 2
    • Speakers & Profile:
      • Vivekananda Karmakar, Consulting Partner – Advanced Analytics, Wipro
      • Angshuman Bhattacharya, CEO and Co-Founder, SIBIA Analytics and Consulting Services PL

      4. Advanced Programme in Data Sciences (APDS), Kolkata

      • About the conference: The conference includes tutorials to softwares like Tableau, Arena, Apache Spark, SPSS, etc., and imparts knowledge on different techniques and tools used to manipulate, interpret, and analyze data.
      • Venue: IIM Calcutta, Diamond Harbour Rd, Joka, Kolkata, West Bengal 700104
      • Purpose: The conference aims to help its attendees understand mathematical methods and statistics for data science and learn technologies like Big Data, Optimization, Visualization, Machine Learning, Econometric Method, Database Management and Warehousing, and Categorical Data Analysis.
      • Whom can you Network with in this Conference:
        • Applicants should be working professionals/self-employed
        • Graduates (10+2+3)/Post Graduation in any discipline with min. 50% marks [aggregate - considering results of all years (e.g. 3 or 4 together)] recognized by UGC/AICTE.
        • Minimum 3 years of work experience (full-time paid employment) post completion of graduation as on Application Closure Date.

      5. FIRE 2019: 11th meeting of the Forum for Information Retrieval Evaluation, Kolkata

      S.NoConference nameDateVenue
      1.Data Science Summit 2018Aug 10, 2018Biswa Bangla Convention Centre, DG Block (Newtown), New Town, Kolkata

      1. Data Science Summit 2018, Kolkata

      • Conference City: Newtown, Kolkata 
      • About: The best minds in Data Science and Artificial Intelligence guided people to build projects from scratch. 
      • Event Date: Aug 10, 2018
      • Venue: Biswa Bangla Convention Centre, DG Block(Newtown), New Town, Kolkata 
      • Days of Program: One 
      • Timings: 10:00 AM - 05:00 PM
      • Purpose: Data Science Summit gave insights into the new products, analytics, and IoT and helped the attendees improve their learning model.
      • Speaker Profile:
        • Arindam Biswas, Head - Digital Intelligence FedEx 
        • Sohan Maheshwar,  Alexa Evangelist Amazon 
        • Dr. Subhankar Dhar, Professor, San Jose State University, etc. 
      • Whom can you Network with in this Conference: Data-driven professionals who give aid you in the industry and are really apt with the latest developments of data science and artificial intelligence. 
      • Registration cost: INR 2500 (may vary)
      • Who were the major sponsors:    
        • NASSCOM

      Data Scientist Jobs in Kolkata, India

      Here’s how one can get started with getting a job as a data scientist in Kolkata:

      • Select an appropriate programming language, preferably R or Python
      • Ensure you're good at maths and stats
      • Master AI and ML
      • Learn how to deal with unstructured data 
      • Try to work with and execute data visualisation
      • Practice these skills in competitions like Kaggle.   

      Here is how one prepares for the data science job:

      • Practice the technical skills and theory of data science 
      • Widen your network by attending conferences, job fairs and meetups 
      • Participate in competitions to know about other data scientists and familiarise yourself with the latest trends of the industry
      • Ensure that your professors or previous employers offer credible referrals 
      • Prepare for the interview 

      The role of a data scientist is to understand the business problem and convert it into an analytical problem. In this existing corporate context, the role of a Data Scientist is becoming even more critical. The data created and organized by the data scientist is used to monitor and deploy patterns, alter marketplace leanings and more. A day in the life of a data scientist involves tackling multiple tasks, collaborating with numerous clients, coming with amazing ideas and developing stunning strategies which can manipulate the industry. Here are some basic responsibilities and duties which you will be expected to perform;

      • To amass statistics from diverse and pertinent sources, both structured and unstructured data 
      • Establish and examine the collected data, and extract what’s important 
      • Create ML methods, programs, and tools to make the data understandable
      • Create algorithms and stats to forecast conceivable consequences.

      As discussed earlier, data scientist is an exciting job opportunity that people want to explore not just for the money and the glamour associated with the profession but also the sheer exhilaration which comes with figuring out innovative insights and developing unique plans. Lucky for you, Kolkata encourages data scientists to explore and experiment in their field and come up with innovative data solutions. Here are some career opportunities you can opt for after getting a degree in data science: 

      • Data Analyst: As a data analyst your job is to study the market trends, detect customer preferences and have a compact impression about the demographics that your business is aiming at. These aid corporates to develop a strong strategy of how exactly would you want to fashion the market and tweak it to suit your needs. It allows one to dictate the kind of saleable ideas you plan to set up and the publicity policies you will have to assume. 
      • Data Researcher: Data scientist has a more problematic job than just spotting and storing marketing trends. As a data expert, your job will entail tasks like assessing massive volumes of data, thinking out patterns, developing a foundation and creating methods grounded on the same. Data experts also have to deal with some software design and hence you must have amazing coding skills. 
      • Data Engineer: As a data engineer your job comprises of assembling data sets, inspecting the business strategies, collaborating with third parties, creating procedures and curating data sets that would ultimately help estimate market trends. As a data engineer, you would also have to plan data related actions, develop radical solutions and study the given material realistically. 

      • Data Architect: A data architect has to frequently work with data scientists and engineers to create elaborate plans for the commercial organization. The data architect is responsible for the mechanisms of the plan. He has access to all the core codes and the data source which he integrates for better-quality results. 
      1. Big Data & Business Analytics - Asia Pacific, Kolkata
      2. StepUp Analytics Kolkata Learn Data Science
      3. Kolkata Data Science Meetup
      4. Analytics Vidhya Kolkata
      5. PyData Kolkata
      6. Kolkata Artificial Intelligence & Deep Learning Online

      Kolkata, as established earlier, is a great space for data scientists and encourages people from the IT sector to join corporate houses and other organizations such as IBM, Square1, Top Gear,  ERM, ERev Max Technologies, PwC, Maven Workforce, BridgeTree etc. to improve earning opportunities. And while it is a very profitable profession, not a lot of people attempt for data science as a career option simply because it involves a lot of hard work and investment. You have to be academically brilliant, great at handling responsibilities and also have a charming personality to woo clients and get more projects. In such an environment, it becomes increasingly difficult to come across and connect with other data scientists in the field. Also, it is important to be aware of contemporaries in the industry, share experiences and learn from each other to create a safe and happy workspace. Here are some ways in which you can meet up with other data scientists and also expand your contacts; 

      • Attend as many data science conferences and academic meetings as you can. This doesn’t only allow you to meet your colleagues but also learn about the latest trends and innovative methods. 
      • Online platforms like LinkedIn and other portals are also a great place to showcase one’s skills and connect with other data scientists and check their caliber. 
      • Technology related events fairs and fests are also places where you can run into data scientists. 
      1. Data Scientist
      2. DataAnalytics Manager
      3. Data Analyst
      4. Data Administrator
      5. Data Architect
      6. Business Analyst
      7. Business Intelligence Manager
      8. Marketing Analyst

      Here’s what companies in Kolkata want from data science candidates:

      • An in-depth knowledge of data science, coding and programming 
      • Mastery over math and statistics 
      • The necessary degrees and certifications 
      • Enough practical experience with projects and conferences 

      Data Science With Python Kolkata, India

      Python is perhaps the most well-known programming platform among coders and data scientists. The reasons for which are listed below; 

      • Python is an open source growing community which is compatible with most operating systems- Windows or Linux or Mac- you can install Python anywhere. 
      • Python doesn’t have a steep learning curve unlike other programming languages we use
      • The OOPS framework adds on to the flexibility and versatility of the platform 
      • Python has an ever-growing community of coders and a diverse range of resources and features to develop solid algorithms

      All kinds of companies and sectors offer jobs to data scientists, and your skills are in demand practically everywhere! Although simply getting a degree in data science is not all, one must have the practical experience, practical knowledge, and understanding of how things work on site. Here are some of the top platforms currently used by most data scientists in the community. Mastering these platforms can hence be very beneficial. 

      • R Programming is an open source software that incorporates top-notch data packages and statistical models 
      • Python is better suited for first timers and budding data scientists because of its user-friendly interface and simple features 
      • SQL is great for multitasking and makes work a lot easier for data scientists 
      • JAVA is optimizable, easy to edit and comprehend. 
      • Download and setup: Go to the download page and install the python on Windows using a GUI installer. Make sure that you check the box asking for ass Python 3.x to PATH that will allow you to use the functionality of python from the terminal.

      You can also try using Anaconda for installing Python. To check the version of Python installed on your windows, you can use the following command:

      python --version

      • Update and install setuptools and pip: For the installation and update of most crucial libraries (3rd party), use the following command:

      python -m pip install -U pip

      Note: For creating an isolated Python environment and pipenv, you have to install virtualenv. Pipenv is a dependency manager for Python.

      To install Python 3 on Mac OS X, you can either directly use a .dmg package and install python from their official website or use Homebrew for the installation of Python and its dependencies. All you need to do is to follow these steps:

      • Install Xcode: Before you install brew, you need to install the Xcode package of Apple. You need to start with the following command: 

      $ Xcode-select --install

      • Install brew: Next step is installing Homebrew which is Apple's package manager. You need to use the following command: 

      /usr/bin/ruby -e "$(curl -fsSL" You can confirm if it is installed by using the command: brew doctor

      • Install Python 3: The last step is installing Python. For that, use the following code:

      brew install python

      • You can confirm the version of Python installed on the computer: python --version

      For creating isolated spaces to run your projects, you can install virtaulenv. This can also be used if you want to use different versions of Python in different projects. 

      What Learners Are Saying

      Ong Chu Feng Data Analyst
      The content was sufficient and the trainer was well-versed in the subject. Not only did he ensure that we understood the logic behind every step, he always used real-life examples to make it easier for us to understand. Moreover, he spent additional time to let us consult him on Data Science-related matters outside the curriculum. He gave us advice and extra study materials to enhance our understanding. Thanks, Knowledgehut!

      Attended Data Science with Python Certification workshop in January 2020

      Lea Kirsten Senior Developer

      The learning methodology put it all together for me. I ended up attempting projects I’ve never done before and never thought I could. 

      Attended Back-End Development Bootcamp workshop in July 2021

      Emma Smith Full Stack Engineer

      KnowledgeHut’s FSD Bootcamp helped me acquire all the skills I require. The learn-by-doing method helped me gain work-like experience and helped me work on various projects. 

      Attended Full-Stack Development Bootcamp workshop in June 2021

      Matt Davis Senior Developer

      The learning methodology put it all together for me. I ended up attempting projects I’ve never done before and never thought I could.

      Attended Full-Stack Development Bootcamp workshop in May 2021

      Matt Connely Full Stack Engineer

      The learn by doing and work-like approach throughout the bootcamp resonated well. It was indeed a work-like experience. 

      Attended Front-End Development Bootcamp workshop in May 2021

      Issy Basseri Database Administrator

      Knowledgehut is the best training institution. The advanced concepts and tasks during the course given by the trainer helped me to step up in my career. He used to ask for feedback every time and clear all the doubts.

      Attended PMP® Certification workshop in January 2020

      Jules Furno Cloud Software and Network Engineer

      Everything from the course structure to the trainer and training venue was excellent. The curriculum was extensive and gave me a full understanding of the topic. This training has been a very good investment for me.

      Attended Certified ScrumMaster (CSM)® workshop in June 2020

      Archibold Corduas Senior Web Administrator

      The teaching methods followed by Knowledgehut is really unique. The best thing is that I missed a few of the topics, and even then the trainer took the pain of taking me through those topics in the next session. I really look forward to joining KnowledgeHut soon for another training session.

      Attended Certified ScrumMaster (CSM)® workshop in May 2020

      Career Accelerator Bootcamps

      Full-Stack Development Bootcamp
      • 80 Hours of Live and Interactive Sessions by Industry Experts
      • Immersive Learning with Guided Hands-On Exercises (Cloud Labs)
      • 132 Hrs
      • 4.5
      Front-End Development Bootcamp
      • 30 Hours of Live and Interactive Sessions by Industry Experts
      • Immersive Learning with Guided Hands-On Exercises (Cloud Labs)
      • 4.5

      Data Science with Python Certification Training in Kolkata

      About Kolkata 

      Kolkata is the capital of the Indian state of West Bengal. This large and vibrant Indian city flourishes amid hard to overcome economic, social, and political problems. Crowds swarm to Kolkata’s book fairs, concerts and art exhibitions, and there is an energetic trading of polemics on walls, which has led to Kolkata being called the city of posters. The city’s energy permeates even to all areas.  

      Data Science with Python Training at KnowledgeHut 

      Data Science with Python opens your career into one of the most promising fields combined with the knowledge of using the fastest growing programming language. KnowledgeHut also helps you offering a variety of courses such as PRINCE2, PMP, PMI-ACP, CSM, CEH, CSPO, Scrum & Agile, MS courses, Big Data Analysis, Apache Hadoop, SAFe Practitioner, Agile User Stories, CASQ, CMMI-DEV and others. 

      Other TraininMore training programs


      Want to cancel?