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Artificial Intelligence End-to-End Course

A compact, hands-on journey through AI, covering ML, DL, Generative AI, and Agentic AI. Learn to build intelligent, real-world systems with modern tools and protocols.

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Ideal for

High schoolers
Students and any professionals

Duration

2 months

Hours per week

6 Hours

Class schedule

3 Sessions Per Week

What you’ll Learn

  • Gain a solid understanding of artificial intelligence and machine learning fundamentals.
  • Learn and apply multiple programming languages essential for AI development, such as Python, SQL, etc.,
  • Master core AI tools and frameworks like TensorFlow, PyTorch, and scikit-learn.
  • Develop skills in data processing, model building, and algorithm optimization.
  • Learn to design, train, and evaluate deep learning models, including convolutional neural networks (CNN)
  • Work on real-world capstone projects that apply knowledge to practical AI problems.

Topics covered by this course

What is Artificial Intelligence?

  • Definition of AI
  • What is Machine Learning?
  • What is Deep Learning?
  • AI vs. Machine Learning (ML) vs. Deep Learning (DL)
  • Milestones: Turing Test, Deep Blue, Alexa, ChatGPT

Evolution and History of AI

  • Brief timeline from symbolic AI to Agentic AI
  • AI winters and breakthroughs (e.g., ImageNet, AlphaGo, GPT)
  • Python Foundations for AI
  • Introduction to Python
  • Working with Python Libraries
    • Introduction to NumPy
    • Introduction to Pandas
    • Introduction to Matplotlib and Data Visualization
  • Descriptive Statistics
  • Data Visualization
  • Probability & Distributions
  • Inferential Statistics
  • Hypothesis Testing
  • Regression Overview
  • Data Wrangling (Pandas)
  • Feature Engineering
  • SQL Basics
  • Categories of Machine Learning
  • Core Algorithms
  • Model Development
  • Performance Metrics
  • Introduction to Deep Learning
  • Neural Network Fundamentals
  • Model Training
  • Optimization & Tuning
  • Convolutional Neural Networks (CNNs)
  • Introduction to Generative AI
  • Autoencoders & VAEs
  • Generative Adversarial Networks (GANs)
  • Diffusion Models
  • NLP & RNN Fundamentals
  • LSTM for Generation
  • Transformers & GPT
  • Foundation of AI Agents
  • Core Properties of an Agent:
  • Types of Agents & Architectures
  • Task Decomposition & Planning
  • Frameworks
  • Intro to MCP, MCP Prompt Architecture & Layers
  • Tool Integration & Execution
  • Infrastructure & Tooling
  • Advanced RAG
  • MLOps & Monitoring
  • Ethics, Safety, and Responsible AI

Get to know us

Our Mission is to bridge the gap between education and industry by offering hands-on workshop, real-world projects, and mentorship from AI Experts.

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