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Data Science with Python Training in Kolkata, India

Get the ability to analyze data with Python using basic to advanced concepts

  • 40 hours of Instructor led Training
  • Interactive Statistical Learning with advanced Excel
  • Comprehensive Hands-on with Python
  • Covers Advanced Statistics and Predictive Modeling
  • Learn Supervised and Unsupervised Machine Learning Algorithms

Description

Rapid technological advances in Data Science have been reshaping global businesses and putting performances on overdrive. As yet, companies are able to capture only a fraction of the potential locked in data, and data scientists who are able to reimagine business models by working with Python are in great demand.

Python is one of the most popular programming languages for high level data processing, due to its simple syntax, easy readability, and easy comprehension. Python’s learning curve is low, and due to its many data structures, classes, nested functions and iterators, besides the extensive libraries, this language is the first choice of data scientists for analysing, extracting information and making informed business decisions through big data.

This Data science for Python programming course is an umbrella course covering major Data Science concepts like exploratory data analysis, statistics fundamentals, hypothesis testing, regression classification modeling techniques and machine learning algorithms.Extensive hands-on labs and an interview prep will help you land lucrative jobs.

What You Will Learn

Prerequisites

There are no prerequisites to attend this course, but elementary programming knowledge will come in handy.

3 Months FREE Access to all our E-learning courses when you buy any course with us

Who should Attend?

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

KnowledgeHut Experience

Instructor-led Live Classroom

Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.

Curriculum Designed by Experts

Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the training.

Learn through Doing

Learn theory backed by practical case studies, exercises and coding practice. Get skills and knowledge that can be effectively applied.

Mentored by Industry Leaders

Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.

Advance from the Basics

Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get reviews and feedback on your final projects from professional developers.

Curriculum

Learning Objectives:

Get an idea of what data science really is.Get acquainted with various analysis and visualization tools used in  data science.

Topics Covered:

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

Hands-on:  No hands-on

Learning Objectives:

In this module you will learn how to install Python distribution - Anaconda,  basic data types, strings & regular expressions, data structures and loops and control statements that are used in Python. You will write user-defined functions in Python and learn about Lambda function and the object oriented way of writing classes & objects. Also learn how to import datasets into Python, how to write output into files from Python, manipulate & analyze data using Pandas library and generate insights from your data. You will learn to use various magnificent libraries in Python like Matplotlib, Seaborn & ggplot for data visualization and also have a hands-on session on a real-life case study.

Topics Covered:

  • Python Basics
  • Data Structures in Python
  • Control & Loop Statements in Python
  • Functions & Classes in Python
  • Working with Data
  • Analyze Data using Pandas
  • Visualize Data 
  • Case Study

Hands-on:

  • Know how to install Python distribution like Anaconda and other libraries.
  • Write python code for defining your own functions,and also learn to write object oriented way of writing classes and objects. 
  • Write python code to import dataset into python notebook.
  • Write Python code to implement Data Manipulation, Preparation & Exploratory Data Analysis in a dataset.

Learning Objectives: 

Visit basics like mean (expected value), median and mode. Understand distribution of data in terms of variance, standard deviation and interquartile range and the basic summaries about data and measures. Learn about simple graphics analysis, the basics of probability with daily life examples along with marginal probability and its importance with respective to data science. Also learn Baye's theorem and conditional probability and the alternate and null hypothesis, Type1 error, Type2 error, power of the test, p-value.

Topics Covered:

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

Hands-on:

Write python code to formulate Hypothesis and perform Hypothesis Testing on a real production plant scenario

Learning Objectives: 

In this module you will learn analysis of Variance and its practical use, Linear Regression with Ordinary Least Square Estimate to predict a continuous variable along with model building, evaluating model parameters, and measuring performance metrics on Test and Validation set. Further it covers enhancing model performance by means of various steps like feature engineering & regularization.

You will be introduced to a real Life Case Study with Linear Regression. You will learn the Dimensionality Reduction Technique with Principal Component Analysis and Factor Analysis. It also covers techniques to find the optimum number of components/factors using screen plot, one-eigenvalue criterion and a real-Life case study with PCA & FA.

Topics Covered:

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

Hands-on: 

  • With attributes describing various aspect of residential homes, you are required to build a regression model to predict the property prices.
  • Reduce Data Dimensionality for a House Attribute Dataset for more insights & better modeling.

Learning Objectives: 

Learn Binomial Logistic Regression for Binomial Classification Problems. Covers evaluation of model parameters, model performance using various metrics like sensitivity, specificity, precision, recall, ROC Cuve, AUC, KS-Statistics, Kappa Value. Understand Binomial Logistic Regression with a real life case Study.

Learn about KNN Algorithm for Classification Problem and techniques that are used to find the optimum value for K. Understand KNN through a real life case study. Understand Decision Trees - for both regression & classification problem. Understand Entropy, Information Gain, Standard Deviation reduction, Gini Index, and CHAID. Use a real Life Case Study to understand Decision Tree.

Topics Covered:

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

Hands-on: 

  • With various customer attributes describing customer characteristics, build a classification model to predict which customer is likely to default a credit card payment next month. This can help the bank be proactive in collecting dues.
  • Predict if a patient is likely to get any chronic kidney disease depending on the health metrics.
  • Wine comes in various types. With the ingredient composition known, we can build a model to predict the Wine Quality using Decision Tree (Regression Trees).

Learning Objectives:

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

Topics Covered:

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

Hands-on:  

  • Write python code to Understand Time Series Data and its components like Level Data, Trend Data and Seasonal Data.
  • Write 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.
  • Write Python code to Use Auto Regressive Integrated Moving Average Model for building Time Series Model
  • Dataset including features such as symbol, date, close, adj_close, volume of a stock. This data will exhibit characteristics of a time series data. We will use ARIMA to predict the stock prices.

Learning Objectives:

A mentor guided, real-life group project. You will go about it the same way you would execute a data science project in any business problem.

Topics Covered:

  • Industry relevant capstone project under experienced industry-expert mentor

Hands-on:

 Project to be selected by candidates.

Meet your instructors

Biswanath

Biswanath Banerjee

Trainer

Provide Corporate training on Big Data and Data Science with Python, Machine Learning and Artificial Intelligence (AI) for International and India based Corporates.
Consultant for Spark projects and Machine Learning projects for several clients

View Profile

Projects

Predict House Price using Linear Regression

With attributes describing various aspect of residential homes, you are required to build a regression model to predict the property prices.

Predict credit card defaulter using Logistic Regression

This project involves building a classification model.

Read More

Predict chronic kidney disease using KNN

Predict if a patient is likely to get any chronic kidney disease depending on the health metrics.

Predict quality of Wine using Decision Tree

Wine comes in various styles. With the ingredient composition known, we can build a model to predict the Wine Quality using Decision Tree (Regression Trees).

Note:These were the projects undertaken by students from previous batches. 

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. 

      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 https://raw.githubusercontent.com/Homebrew/install/master/install)" 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. 

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      Front End Developer
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      FAQs

      The Course

      Python is a rapidly growing high-level programming language which enables clear programs on small and large scales. Its advantage over other programming languages such as R is in its smooth learning curve, easy readability and easy to understand syntax. With the right training Python can be mastered quick enough and in this age where there is a need to extract relevant information from tons of Big Data, learning to use Python for data extraction is a great career choice.

       Our course will introduce you to all the fundamentals of Python and on course completion you will know how to use it competently for data research and analysis. Payscale.com puts the median salary for a data scientist with Python skills at close to $100,000; a figure that is sure to grow in leaps and bounds in the next few years as demand for Python experts continues to rise.

      • Get advanced knowledge of data science and how to use them in real life business
      • Understand the statistics and probability of Data science
      • Get an understanding of data collection, data mining and machine learning
      • Learn tools like Python

      By the end of this course, you would have gained knowledge on the use of data science techniques and the Python language to build applications on data statistics. This will help you land jobs as a data analyst.

      Tools and Technologies used for this course are

      • Python
      • MS Excel

      There are no restrictions but participants would benefit if they have basic programming knowledge and familiarity with statistics.

      On successful completion of the course you will receive a course completion certificate issued by KnowledgeHut.

      Your instructors are Python and data science experts who have years of industry experience. 

      Finance Related

      Any registration canceled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of a written request for refund. Kindly go through our Refund Policy for more details.

      KnowledgeHut offers a 100% money back guarantee if the candidate withdraws from the course right after the first session. To learn more about the 100% refund policy, visit our Refund Policy.

      The Remote Experience

      In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.

      Minimum Requirements: MAC OS or Windows with 8 GB RAM and i3 processor

      Have More Questions?

      Data Science with Python Certification Course in Kolkata

      Kolkata is the capital of the Indian state of West Bengal. This large and vibrant Indian city flourishes amid seemingly hard to overcome economic, social, and political problems. Its citizens exhibit a great joie de vivre that is reflected in a fondness for art and culture and a high level of intellectual vivacity and political awareness. 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.? Yet for all of Kolkata?s vitality, many of the city?s residents live in some of the worst conditions, far removed from the cultural milieu. The city?s energy nevertheless infiltrates even to the poorest areas, as a large number of Kolkatans sincerely support the efforts of those who minister to the underprivileged. Qualified people seeking new challenges can thrive with certifications that include CompTIA Cloud Essentials, Certified Scrum Master and others. Note: Please note that the actual venue may change according to convenience, and will be communicated after the registration.