AI Fundamentals and Machine Learning

Comprehensive training designed for professionals

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Course Overview

Explore the course outline and contact our advisors about prerequisites, practical work, and current availability.

For the current syllabus, prerequisites, fees, and batch availability, contact our training advisors.

Meet Your Instructor: Dr. Farhan Ali

Deep learning specialist with research background in neural networks, TensorFlow and AI systems.

Course Lectures

Course Content

1 AI Concepts & History
2 Python & Math Foundations for AI
3 Supervised Learning Essentials
4 Unsupervised Learning Essentials
5 Neural Networks Introduction
6 Natural Language Processing Basics
7 Computer Vision Basics
8 AI Project: From Idea to Demo

AI Concepts & History

2 hours

Lecture 1 of 8

What AI really is: machine learning, deep learning, and generative AI in historical context.

Python & Math Foundations for AI

2 hours

Lecture 2 of 8

NumPy essentials, linear algebra intuition, and probability basics for machine learning.

Supervised Learning Essentials

2 hours

Lecture 3 of 8

Regression and classification with scikit-learn on real datasets.

Unsupervised Learning Essentials

2 hours

Lecture 4 of 8

Clustering, dimensionality reduction, and finding patterns without labels.

Neural Networks Introduction

2 hours

Lecture 5 of 8

Perceptrons to multi-layer networks: build and train your first neural net.

Natural Language Processing Basics

2 hours

Lecture 6 of 8

Text preprocessing, embeddings, and sentiment analysis with modern libraries.

Computer Vision Basics

2 hours

Lecture 7 of 8

Image classification with CNNs using pre-trained models and transfer learning.

AI Project: From Idea to Demo

3 hours

Lecture 8 of 8

Scope, build, and present a working AI demo solving a real problem.

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Eligibility Criteria

No prior AI experience needed. Basic Python helpful.

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AI Fundamentals and Machine Learning