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Foundation of AI, ML, NN and GenAI + Capstone Project
206 students

Foundation of AI, ML, NN and GenAI + Capstone Project

Learn AI, ML, Neural Networks & Generative AI from scratch with real-world concepts and a capstone approach
Created bySandeep Soni
Last updated 1/2026
English

What you'll learn

  • Understand how AI systems differ from traditional software
  • Identify different types of AI and real-world AI workloads
  • Clearly explain Machine Learning concepts, algorithms, and models
  • Understand how ML models are trained, evaluated, and used
  • Build and use a basic ML model using Python
  • Understand Artificial Neural Networks and Deep Learning
  • Learn key neural network architectures
  • Understand Generative AI concepts and use cases
  • Learn how Autoencoders, GANs, Diffusion models, and Transformers work
  • Understand LLMs, SLMs, fine-tuning, and AI agents

Course content

6 sections21 lectures6h 19m total length
  • Getting Started with AI,ML, NN and Deep Learning12:07
  • Foundation of AI, ML
  • AI Systems vs Non - AI System9:04
  • Quiz
  • Types of Artificial Intelligence5:46
  • Quiz
  • Common AI Workloads and Use cases40:25

    Identify core AI workloads—machine learning, computer vision, natural language processing, speech, document intelligence, anomaly detection, and generative AI—and learn how to select the right specialization for cross-industry use cases.

  • Quiz

Requirements

  • No prior AI, ML, or GenAI experience required
  • Basic computer knowledge is enough
  • Basic Python knowledge is helpful but not mandatory
  • A willingness to learn concepts step-by-step
  • Curiosity about how intelligent systems are built

Description

Artificial Intelligence is no longer optional—it is becoming a core skill across industries. However, most learners struggle because AI courses are either too mathematical, too abstract, or jump straight into tools without building strong fundamentals.

This course solves that problem.

Foundation of AI, ML, NN & GenAI + Capstone Project is a carefully structured beginner-to-intermediate course that helps you understand how AI systems actually work, from classical Machine Learning to modern Generative AI and Large Language Models.

You’ll start by learning what AI truly is, how AI systems differ from traditional software, and where AI is used in real-world scenarios. From there, you’ll build a solid foundation in Machine Learning—understanding algorithms, models, training workflows, evaluation methods, and career paths.

Next, you’ll move into Artificial Neural Networks and Deep Learning, creating the bridge to Generative AI. You’ll then explore GenAI concepts, understand different GenAI models, and learn how technologies like Autoencoders, GANs, Diffusion Models, and Transformers power today’s AI applications.

The course also covers LLMs, fine-tuning, AI agents, major AI labs, and ethical AI principles, giving you industry-relevant awareness that most beginner courses miss.

This course focuses on clarity, structure, and real-world understanding, not just buzzwords. Whether you want to enter AI, upgrade your skills, or confidently talk about GenAI in professional settings—this course gives you the foundation you need.

Who this course is for:

  • Beginners with no prior AI/ML background
  • Students and fresh graduates exploring AI career paths
  • Software developers who want to transition into AI/ML or GenAI
  • Working professionals curious about how modern AI systems actually work
  • Non-technical professionals who want to understand AI concepts, GenAI, and LLMs clearly
  • Anyone planning to move into Data Science, ML Engineering, or GenAI roles