Foundations of Artificial Intelligence & Machine Learning

This comprehensive training program is designed to equip participants with a strong foundation in Artificial Intelligence (AI), Machine Learning (ML), and modern AI technologies. The course combines theoretical knowledge with practical applications, enabling learners to understand key AI concepts and apply them in real-world scenarios.

Program Modules:

1- Introduction to Artificial Intelligence & Machine Learning
Overview of AI and its applications across industries
Core principles of Machine Learning and real-world use cases

2- Deep Learning Basics – Neural Networks, CNNs, RNNs
Understanding the fundamentals of neural networks
Introduction to Convolutional Neural Networks (CNNs) for image and vision tasks
Recurrent Neural Networks (RNNs) for sequential and time-series data

3- Types of AI: Supervised, Unsupervised, Reinforcement Learning
Supervised Learning: concepts, algorithms, and applications
Unsupervised Learning: clustering and dimensionality reduction
Reinforcement Learning: decision-making and reward-based systems

4- Introduction to Data Science
Data collection, cleaning, and pre-processing
Exploratory Data Analysis (EDA) and visualization
Role of data in building AI-driven insights

5- Python for AI
Python fundamentals for AI development
Libraries and tools: NumPy, Pandas, Matplotlib, Scikit-learn
Hands-on exercises in model building and evaluation

6- Introduction to Generative AI & LLMs
What is Generative AI and how it is transforming industries
Introduction to Large Language Models (LLMs) such as GPT
Use cases in text generation, chatbots, and creative AI applications