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.
Get acquainted with various analysis and visualization tools such as Matplotlib and Seaborn
Understand the behavior of data;build significant models using concepts of Statistics Fundamentals
Learn the various Python libraries to manipulate data, like Numpy, Pandas, Scikit-Learn, Statsmodel
Use Python libraries and work on data manipulation, data preparation and data explorations
Use of Python graphics libraries like Matplotlib, Seaborn etc.
ANOVA, Linear Regression using OLS, Logistic Regression using MLE, KNN, Decision Trees
There are no prerequisites to attend this course, but elementary programming knowledge will come in handy.
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Learn theory backed by practical case studies, exercises and coding practice. Get skills and knowledge that can be effectively applied.
Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.
Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.
Get reviews and feedback on your final projects from professional developers.
Get an idea of what data science really is.Get acquainted with various analysis and visualization tools used in data science.
Hands-on: No hands-on
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.
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.
Write python code to formulate Hypothesis and perform Hypothesis Testing on a real production plant scenario
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.
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.
Understand Time Series Data and its components like Level Data, Trend Data and Seasonal Data.
Work on a real- life Case Study with ARIMA.
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.
Project to be selected by candidates.
With attributes describing various aspect of residential homes, you are required to build a regression model to predict the property prices.
This project involves building a classification model.
Predict if a patient is likely to get any chronic kidney disease depending on the health metrics.
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).
In 2012, Data Scientist was named as the ‘Sexiest Job of the 21st century’ by the Harvard Business Review. The reason behind this popularity is data. Over 2.5 quintillion bytes of data are created every single day and companies are continuously figuring out a way to make the best use of this data. Chennai is one of the metro cities of India and is home to several leading companies, including Crayon Data, Shell, FIS, Hinduja Tech, Ideas2IT, tvs, eHelium, Mindtree, etc. All these companies are looking for expert data scientists to help them make decisions on product and operating metrics.
The top skills that are needed to become a data scientist include the following:
If you want to become a successful Data Science professional, you need to incorporate the following behavioral traits:
The 5 proven benefits of being a Data Scientist include:
The 4 must-have business skills required to become a data scientist:
If you are looking for a job as a data scientist and want to brush up your data science skills, here is what you need to do:
We live in a world of data. Your investment in the stock market is data, your medical diagnosis is data, your browsing history is data and the list goes on. Most companies in Chennai collect data for their benefit. Leading companies in Chennai such as Crayon Data, Shell, FIS, Hinduja Tech, Ideas2IT, tvs, eHelium, Mindtree, etc. are looking for expert data scientists to improve product performance, building prediction models, affinity maps, and cluster analysis, etc.
To practice your data science skills, you can try one of the following datasets that are categorized according to their difficulty level:
Follow the below-mentioned steps to become a successful data scientist:
Here are a series of steps you need to follow to become a data scientist:
Getting a degree in Data Science from a reputed institution can help you get ahead in your career. The advantages of getting a degree in Data Science include:
The below-mentioned scorecard will help you determine if you need a Master's degree or not. If you get a score of more than 6 points, a Master's degree in Data Science is required.
Programming knowledge is the most basic and essential skill required to get a job in the field of data science. Here is why:
In Chennai, a Data Scientist earns a pay of Rs. 8,19,815.
Data Scientist working in Chennai earn an average of about Rs. 8,19,815 as compared to Rs. 5,89,851 in Pune.
The earning of a Data Scientist is Rs. 8,19,815 per year as compared to Rs. 6,13,889 earned by a Data Scientist working in Hyderabad.
The annual earnings of a Data Scientist in Chennai is Rs. 8,19,815 as compared to Rs. 6,15,496 in Bangalore.
Data Scientist in Chennai earns about Rs. 8,19,815 every year. Data Scientists working in Coimbatore earn Rs. 3,60,000 per year.
The average annual salary of a Data Scientist in Chennai is about Rs. 8,19,815 every year as opposed to Data Scientists working in Madurai who earn Rs. 13,05,000 per year.
Many organizations in Chennai are looking for data scientists. There are several job listings in various portals offering handsome salaries to data scientists. So, it is clear that the demand for Data Scientists in Chennai is high.
If you are a Data Scientist in Chennai, you can stay assured that the city has more to offer than just the beaches and the beautiful weather. There are a number of companies that are looking to hire data scientists. This means, there will be plenty of job opportunities for you to display your expertise in data science.
In Chennai, there are several advantages of being a Data Scientist apart from the salary. There are several firms in the city that are searching for data scientists who can leverage data and help the business grow. This offers data scientists many opportunities for tremendous job growth in this city. The presence of several high tech companies in the city has also enhanced the playing field for data scientists who can explore their options in a variety of sectors from technology to pharma to government positions that use data science to meet business objectives.
If you are in Chennai and looking for a Data Scientist job, you can apply at Wipro Ltd, Wabco, Avira Operations GmbH & Co. KG, Ford Global Business Services, Vestas, Ericsson and many more.
|1.||2nd National Conference on Data Science and Intelligent Information Technology NCDSIIT 18||6-7th April, 2018||Rajalakshmi Institute of Technology, Kuthambakkam, Chennai|
|2.||Artificial Intelligence Summit, Chennai, India||11 May, 2019|
Seminar Hall, Cresent Innovation & Incubation Council B S A Cresent Institute of Science and Technology, Seethakathi Estate, GST Road,Vandalur, Chennai-600048.
1. 2nd National Conference on Data Science and Intelligent Information Technology NCDSIIT 18, Chennai
2. Artificial Intelligence Summit, Chennai, India
To get a job in the field of data science, you need to follow the below-mentioned learning path:
If you are preparing for a data scientist job, you need to follow the below-mentioned steps:
Here are the major roles and responsibilities of a Data Scientist:
Cognizant - CTS, Tata Consultancy Service - TCS, HCL Technologies, Accenture, Hexaware Technologies, Aspire Systems, Nokia, and Computer Science Corporation - CSC, etc. are some of the leading companies in Chennai looking for skilled data scientists. The average salary for a Data Scientist is ₹11,14,947 in Chennai, India.
The Data Science career path is as follows:
Business Intelligence Analyst: It is the responsibility of a business intelligence analyst to figure out how the business works and its standing in the current market. He also needs to perform data analysis on how market trends affect the business.
Data Mining Engineer: A job of data mining engineer includes examining the collected data and creating sophisticated algorithms required for data analysis.
Data Architect: A data architect creates blueprints with the help of developers and system designers that are used for integrating, centralizing, maintaining, and protecting the data sources.
Data Scientist: A Data Scientist is responsible for analyzing the data, creating a hypothesis, and exploring patterns and relationships present in the data. They also provide insights from data by creating systems and algorithms.
Senior Data Scientist: A senior data scientist has to determine the future needs of the business and make sure that all the projects are shaped in such a way as to reach the goal of the organization.
Given below are the top professional organizations for data scientists in Chennai –
The most effective ways to get hired as a data scientist are referrals. Some of the other ways to network with data scientists are:
There are several career options for a data scientist –
There are some tools and software that you must master to get preferred over other candidates:
When it comes to data science, python is the most popular and preferred programming language. Here is why:
Python has multiple facets that can be used in the field of data science. It is a structured and object-oriented programming language. Several libraries and packages come in handy while working in the field of data science. The syntax of Python is easy to read, understand, and write. The reason why so many data scientists are attracted towards the programming language is a large number of analytical libraries and packages that comes with it. There are several resources available on the language like documentation, tutorials, videos that can be used by data scientists whenever they are stuck.
The 5 most popular programming languages used for Data Science include:
Here is what you need to do to download and install Python 3 on Windows:
python -m pip install -U pip
To download and install Python 3 on Mac OS X, all you need to do is:
To confirm if python was installed, use the command: python --version
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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.
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
There are no restrictions but participants would benefit if they have basic programming knowledge and familiarity with statistics.
Yes, KnowledgeHut offers virtual training.
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.
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.
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