Python For Data Analytics
IIIT-Bhagalpur offers Certified Project Based Learning Program in “Python for Data Analytics”

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This Python Programming Course covers both concepts and project of Python like Data Structures & Types, writing python scripts, sequence and file operations, Graphs & Plots, Data Wrangling, Statistical Computation, etc. This course will also offer practical exposure to some of the important and widely used Python Programs like Pandas, Numpy, Matplotlib, Anaconda, Scipy etc.
Especially developed in collaboration with academia & AI Industry experts to reskill and retool working professionals towards Artificial Intelligence space.This program offers the benefits of Experienced Faculty Led Sessions: Live-Interactive Online classes and Project based Learning. Program content & structure designed in collaboration with Industry experts.

Session: 2 hours/day - 2 days a week (weekend) Batch Size: 50 Students

10
Interactive Live Modules

30
Hours of Learning

2
Industry Projects

15
Instructor Led Sessions

Python is a very powerful open-source language that has powerful libraries for data manipulation and analysis. For a longtime, Python has been used in scientific computing and highly quantitative domains such as Healthcare, Transportation, Retail & Finance. As of today, it is the most preferred language for Artificial Intelligence, Robotics and Web Development.

Syllabus Structure

What you will learn from this course


Module 1:

Module 1 : Introduction to Python Programming
  • Installation of Python
  • Interactive Shell
  • User Interface or IDE , Pycharm, Eclipse, Visual Studio
  • Program structure in Python
  • Execution steps
  • Executable or script files.

Module 2:

Module 2 : Introduction to Packages
  • Installation of packages
  • Using Anaconda, Numpy Pandas
  • Scipy, Matplotlib

Module 3:

Module 3 : Data Structure and Types in different Packages
  • Array
  • Lists
  • Tuples
  • Strings
  • Variables
  • Arithmetic and Logical operations
  • Date and Time

Module 4:

Module 4 : Statements and controls in Python
  • Assignments, Expressions and prints
  • If tests and conditional logic
  • While and For Loops
  • Iterations and Comprehensions

Module 5:

Module 5 : Processing Texts
  • Texts and Strings
  • Converting Strings to numbers
  • Converting numbers to strings
  • Concatenation of strings

Module 6:

Module 6 : Graphs and Plots
  • Matplotlib package
  • Interactive graphs and Image files
  • Plotting graphs
  • Lines and Markers
  • Colors
  • Plotting several graphs in one figure
  • Controlling the graph
  • Histogram and different graphs

Module 7:

Module 7 : File Operations
  • Opening a file
  • Closing a file
  • searching inside text file
  • Working with csv files
  • Working with Binary files

Module 8:

Module 8 : Data Wrangling
  • Filtering out missing data.
  • Filling in missing data
  • Finding outliers.
  • Re-shaping and Pivoting
  • Removing duplicates.
  • Replacing values.
  • Web Scraping

Module 9:

Module 9 : Statistical Computation
  • Correlation & Co-variance.
  • Polynomials & Liner regression.
  • Statistical tests

Module 10:

Module 10 : Database Connection
  • Files versus Database
  • Visual Studio and SQl
  • SQL queries in Python projects

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Our Faculty

A.K Sinha
Lead Instructor
DR. DEEPTI YADAV
Instructor
KUNAL GERA
Instructor
DR. R. BHATTACHARYYA
Instructor
DR. SANDEEP RAJ
Instructor
DR. DILIP K. CHOUBEY
Instructor

Testimonials

Perfect for beginner level. All the concepts with code and parameter wise have been explained excellently. Overall best course in making anyone eager to learn from basics to handle advances with ease.

- Mohini Soni

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

- Himani Pargaien

Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.

- Prairit Mathur

Course FAQ

Why Enroll for the Python for Data Analytics Program?

Everyone wants to succeed in business, but this fast-moving digital world requires new skills. Whether you are a manager, a product engineer, a business analyst, a consultant, or a student, you will benefit from the skills to gain insights from your data through analytics. As the top-ranked programming language, Python allows you to analyze very large data sets and create visualizations to move you and your organization forward. Whether you are a first-time programmer or someone with experience in other languages, the Python for Data Analytics certificate program will give you the foundation to move ahead with confidence.

Who Is This Program For?

Engineers, Marketing & Sales Professionals, Freshers, Domain Experts, Software & IT Professionals

What skills do I need to become a data analyst?

The core skills for data analysis work include: SQL, Programming in Python (or R), Data Cleaning, Data Analysis, Data Visualization, Statistical Analysis etc.

How Python is used in data analytics?

That makes Python a must-have tool not only for data analysis but for all data science. You can make the data more accessible and easier-to-use by means of creating various charts and graphics, as well as web-ready interactive plots. Yes, Python provides you with the capability to get a good sense of data.

What are the Eligibility criteria?

The minimum eligibility criteria for a Data Analytics course is Bachelor's degree with at least 50% marks in aggregate or equivalent preferably in Science or Computer Science from a recognised university, No coding experience required.
Required Skill-Set for Data Analytics - To be good at data analysis, one needs to have strong analytical and numerical skills and must have a thorough understanding of computer software(s) like Querying Language (SQL, Hive, Pig), scripting Language (Python, Matlab), Statistical Language (R, SAS, SPSS), and Excel.

What will be learning outcome of this course?

  • Participants will be able to understand and use python data science libraries as a tool for data analytics
  • Participants will be able to create Python codes for the above techniques
  • Participants will be create visualizations using python
  • Job opportunities: Data Analyst, Data Scientist, Data Engineer, Product Analyst, Machine Learning Engineer, Decision Scientist

What if I miss the class?

Hey, No need to worry! Our in-house Learning Management System will provide you with recordings of every lecture.
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