🔔 Upcoming
Programs

Upcoming Programs

100 hrs Offline Training on Data Science
Sep 5, 2025, IIIT Ongole, AP, in association with Excer Edutech Pvt Ltd, Hyderabad

Trainer to Trainer (Online) program on AI Data Science
From Sep 18, 2025, in association with ASHA, Andhra Pradesh

Python for AI & Data Science

This course is a comprehensive introduction to Python programming tailored for AI and Data Science. Covering everything from Python basics and control flow to advanced data structures, OOP, and essential libraries for machine learning and deployment, it is designed for beginners and aspiring data professionals. Through hands-on modules and a capstone project, learners will gain practical skills to build, evaluate, and deploy AI solutions using Python.

Course Modules

Module 1: Getting Started with Python for AI
  • Why Python for Data & AI
  • Jupyter notebook, Google Colab
  • Syntax, variables, data types
  • Input/output, basic error handling
Module 2: Control Flow and Functions
  • Operators, if/else, loops
  • Defining & calling functions
  • Arguments, return values, scope
  • lambda, map, filter, zip, enumerate
Module 3: Pythonic Data Structures
  • Lists, tuples, dictionaries, sets
  • List/dict/set comprehensions
  • Working with nested structures (like JSON)
Module 4: Data-Centric Python Programming
  • File operations (CSV, JSON, Excel)
  • pandas: Series, DataFrames, basic wrangling
  • numpy: arrays, reshaping, indexing
Module 5: Object-Oriented Programming in AI Context
  • Classes, __init__, attributes
  • Methods, static/class methods
  • Inheritance, polymorphism
  • Encapsulation, abstraction
  • AI related examples
Module 6: Intermediate Python for AI
  • Exception handling: real use in model evaluation
  • Iterators, generators
  • Decorators: logging model training
  • Context managers
  • Working with time
Module 7: Data Science & AI Libraries
  • pandas, numpy, matplotlib, seaborn for EDA and visualizations
  • scikit-learn: ML algorithms and preprocessing
  • keras /tensorflow
  • re module: regex in NLP
  • Streamlit, Python Flask for ML model deployment
Module 8: Applied Python Tools
  • requests, beautifulsoup: Web data extraction
  • Serialization: pickle, joblib, json
  • Logging, testing: unittest, pytest
  • Virtual environments, pip, requirements.txt
Module 9: Capstone Project
  • End-to-end project on Simple Linear Regression involving:
  • Data loading and cleaning
  • EDA and feature engineering
  • ML model training
  • Evaluation and reporting
  • GitHub repo submission
  • Streamlit Cloud Deployment
Enroll Now