A BITS Pilani Alumnus Initiative

Data Analysis with Python

Learn data analysis and visualization using Python libraries. Transform raw data into actionable insights. Best course for beginners to start their data science journey with Python.

60 hours

Duration

Beginner

Level

Live

sessions

Enroll NowFree Demo Class
Data Analysis and Visualization

High Demand

Data Science Skills

Course Pricing

Limited seats per batch
Indian Students (Batch)?29,999
International Students (Batch)$499
Personalised 1-on-1 SessionsContact for Pricing

Course Overview

What You'll Learn

  • Python syntax and internals
  • Data types, variables, and operators
  • Control structures and loops
  • Functions and modular programming
  • File handling and data manipulation
  • Exceptions handling, Regex in Python
  • NumPy for numerical computing
  • Pandas for data manipulation and analysis
  • Data visualization with Matplotlib and Seaborn
  • Web Scraping basics
  • Exploratory Data Analysis (EDA) techniques
  • Case Studies and Portfolio Projects

Prerequisites

  • No prior programming experience required
  • Willingness to learn and practice

Career Opportunities

  • Data Analyst
  • Business Intelligence Analyst
  • Data Scientist

Why choose us?

Continuous Assignments
Doubt clearing
Mock interviews
Real life projects

Course Curriculum

Week 1-2
Python Fundamentals
  • Jupyter Notebook, Google colab
  • Introduction to Python, basic syntax and indentation
  • Internal working of Python and Memory Management
  • Variables, data types, and operators
  • Input/output operations
Week 3
Control Structures
  • Conditional statements (if, elif, else)
  • Loops (for, while)
  • Break and continue statements
  • Nested loops and conditions
  • Hands-on: Number guessing game
Week 4
Data Structures
  • String manipulation and methods
  • Lists and Tuples
  • Dictionaries, Sets and their operations
  • List & Dictionary comprehensions
  • Shallow copy and deep copy
Week 5
Functions and Modules
  • Function definition and calling
  • Parameters and return values
  • Lambda functions, map, filter, reduce
  • Iterators, Generators & Decorators
  • Inbuilt and user-defined modules
  • Hands-on: Simple Banking Application
Week 6
File handling, Exception handling and Regular Expressions
  • File handling operations
  • Exception handling techniques
  • Regular expressions using regex
Week 7
Numpy
  • Array Creation, Array Operations, Indexing, Slicing
  • Numpy Functions and Methods, Array Broadcasting
  • Logical Operations on arrays
  • Solving equations using Numpy
  • Date, time and Basics Statistics using Numpy
  • Loading & Saving data
  • Mini project
Week 8
Pandas
  • Introduction to Pandas
  • Series and Operations on Series
  • DataFrame and Operationson Dataframes: Indexing, Filtering, Sorting
  • Filtering and Extracting data using Pandas
  • Handling CSV and Excel files with Pandas
  • Data merging and joining techniques
  • Handling missing data and outliers
  • Groupby and aggregation with Pandas
  • Data transformation and manipulation
Week 9
Data Visualization & Basic Web Scraping for Data Analysis
  • Pandas built-in data visualization
  • Data visualization with Matplotlib
  • Advanced plotting with Seaborn
  • Introduction to requests & BeautifulSoup
  • Parsing HTML content using BeautifulSoup
  • Finding and Selecting Particular Elements with BeautifulSoup
  • Extracting from website
Week 10
EDA, Case Studies & Revision
  • Exploratory Data Analysis (EDA) techniques
  • Case Studies and Portfolio Projects
  • Revision

Free Learning Resources

Get started with our free video tutorials and learn the basics before enrolling in our comprehensive courses.

Python Basics
06:41

Python Basics

Learn Python fundamental concept - Variables & Memory Management

YouTube
Advanced concepts in Python
10:09

Advanced concepts in Python

Shallow copy & Deep copy

YouTube
Loops in Python
06:43

Loops in Python

for loop

YouTube