top of page

Python

Image by Brecht Corbeel

✅ Course Highlights

  • 100% Practical Training

  • Job-Oriented Curriculum

  • Interview Questions

  • Beginner to Advanced Coverage
     

Duration: 45 Days
contact :9491882804

Module 1: Introduction & Setup
 

  • Course overview & common student confusions

  • Installing Python

  • Installing PyCharm IDE

  • PyCharm basics (interface, theme, font settings)

  • Introduction to Jupyter Notebook

  • Installing Anaconda / Jupyter Notebook setup

  • Jupyter Notebook interface & features

  • Creating and running first notebook (.ipynb)

  • Markdown vs Code cells

​

Module 2: Python Fundamentals
 

  • Variables and their usage

  • Data types in Python

  • Naming rules for variables

  • Type conversion (constructors)

  • Print function (complete understanding)
     

Module 3: Strings & Operations
 

  • String basics & accessing values

  • Slicing and multiple value access

  • Reverse & modified reverse methods

  • Split method

​

Module 4: Operators & Input
 

  • Arithmetic operators

  • Assignment operators

  • Comparison operators

  • Logical operators

  • BODMAS rule (operator precedence)

  • Input function (deep dive)

Python

Module 5: Conditional Statements
 

  • IF statements

  • IF–ELIF ladder

  • Nested IF conditions

​

Module 6: Loops (Core Programming)
 

  • For loops

  • While loops

  • Nested loops

​

Module 7: Lists (Data Handling Core)

​

  • List introduction

  • Modify, add, append values

  • Remove/move elements

  • Looping through lists

  • Sorting, join, reverse operations

​

Module 8: Tuples

​

  • Tuple basics

  • Add/change values (concept clarity)

  • Looping in tuples

  • Index & count methods

  • List vs Tuple differences

​

Module 9: Error Handling & Functions

​

  • Error handling (try-except)

  • User-defined functions

  • Types of functions

  • Passing multiple parameters

  • Variable scope (local vs global)

​

Module 10: Dictionaries

​

  • Dictionary introduction

  • Access keys & values

  • Modify data

  • Remove, delete, clear operations

​

Module 11: Sets
 

  • Set introduction

  • Set operations & methods

​

Module 12: Introduction to Pandas
 

  • What is Pandas?

  • PIP concept (package installation)

  • Reading CSV files

  • Reading Excel files

Module 13: DataFrame Operations
 

  • Column extraction (head, tail)

  • Rename columns

  • Drop/delete columns

  • Insert new columns

  • Change data types (astype, to_datetime)

  • Data size optimization techniques
     

Module 14: Advanced Pandas
 

  • Looping in DataFrames

  • Concatenate datasets

  • Merge (lookup operations like SQL joins)

  • Data filtering (between, isin)

  • loc & iloc usage

  • Remove duplicates

  • Handle missing values (dropna, fillna)

  • Update/change values

​

Module 15: Data Analysis & Reporting
 

  • Aggregation functions: Sum, Count, Unique

  • nlargest, nsmallest

  • Value counts

  • GroupBy (report generation)

  • Looping in GroupBy
     

  • Module 16: NumPy
     

  • Arrays & indexing

  • Mathematical operations

  • Aggregations (sum, mean, min, max)

    Module 17: Data Visualization
     

  • Matplotlib (Line, Bar, Pie charts)

  • Seaborn (advanced visualizations)

  • Creating analytical reports

​

Module 18: Excel Automation using Python

  • Read & write Excel files

  • Automate reports

  • MIS reporting using Python

​

Module 19: Real-Time Projects

  • Sales Data Analysis

  • HR Analytics

  • Finance Dashboard

  • End-to-End Project Implementation

bottom of page