What is FOUNDATIONS OF AI, MACHINE LEARNING & DATA SCIENCE?
A fast-track practical training program designed to introduce learners to Artificial Intelligence, Machine Learning, Data Science, Python Programming, Data Analytics, and Generative AI. This beginner-friendly program builds a strong foundation through hands-on labs, mini projects, and real-world datasets, enabling learners to develop practical AI and data-driven problem-solving skills. Ideal for students, fresh graduates, and working professionals looking to start a career in AI, Machine Learning, Data Science, and Analytics
This program is designed to take you from a complete beginner to a job-ready professional. We focus on practical skills, industry best practices, and the latest tools used by top tech companies globally.
Course Syllabus
PHASE 1 — AI & Programming Foundations
Module 1: Introduction to AI & Data Science
- Introduction to Artificial Intelligence
- What is Data Science?
- AI vs Machine Learning vs Deep Learning vs Generative AI
- Real-world AI applications
- Data science lifecycle
- AI career opportunities
- Development environment setup
- Tools: Python, Jupyter Notebook, Google Colab, VS Code
Module 2: Python Programming for AI
- Python fundamentals: variables, data types, operators, expressions
- Conditional statements & loops
- Functions
- Lists, tuples, dictionaries & sets
- File handling
- Intro to object-oriented programming
- NumPy basics
- Pandas basics
- Labs: Python programming exercises, data processing, simple automation scripts
PHASE 2 — Data Analytics & Machine Learning
Module 3: Data Analytics & Visualization
- Data collection & preparation
- Data cleaning
- Exploratory data analysis (EDA)
- Data visualization
- Business insights
- Intro to dashboards
- Labs: Data cleaning, EDA, sales & customer data visualization
- Tools: Pandas, Matplotlib, Seaborn
Module 4: Machine Learning Fundamentals
- Introduction to machine learning
- Supervised learning: regression & classification
- Unsupervised learning: clustering
- Model training & testing
- Model evaluation
- Feature engineering basics
- Labs: Customer churn prediction, house price prediction, student performance prediction
- Tools: Scikit-learn
PHASE 3 — Generative AI & Mini Project
Module 5: Introduction to Generative AI
- Introduction to Large Language Models (LLMs)
- Prompt engineering basics
- ChatGPT, Gemini & Claude
- AI-assisted content generation
- AI for coding & documentation
- Responsible AI & AI ethics
- Labs: AI-powered chatbot, AI content generator, AI resume builder
Module 6: Mini Project & Career Preparation
- Practical AI project (choose one):
- Customer prediction system
- Sales analytics dashboard
- Movie recommendation system
- AI chatbot
- Basic data analysis project
Frequently Asked Questions
Do I need prior experience?
No, this course starts from the basics. However, a general curiosity about technology is always helpful.
Will I get a certificate?
Yes, upon successful completion of the course and projects, you will receive a verified industry-recognized certificate from Next Gen Pro.