PROFESSIONAL DIPLOMA IN MACHINE LEARNING & A I WITH CHATGPT

Professional Diploma in Machine Learning & A I with ChatGPT “The key to artificial intelligence has always been the representation.” —Jeff Hawkins

The simulation of human intellect by machines is known as “artificial intelligence”, machines that display human characteristics such as learning, problem-solving and decision making. AI aims to build smart machines capable of performing tasks that generally require human intelligence. AI typically refers to a broader concept where the idea is that machines can execute tasks smartly.  While machine learning is a sub field of AI  that gives machines the ability to learn and adapt through experience.

In today’s world, firms that want to gain a competitive advantage employ various kinds of artificial intelligence to better understand their consumers and to increase their knowledge of a customer’s needs.

This diploma in Machine Learning & Artificial Intelligence with Chat GPT delves into Expert systems, Machine Learning, Deep learning, Reinforcement learning, Data Mining, and Statistics. Using technologies such as Python, it walks a business through all the steps, from model training to deploying models into production that is required to begin leveraging the potential of AI. It also explores the future possibilities and challenges of AI.

AI Foundations (3 Weeks)

• History of AI
• Current state-art-of-the AI tools
• Application of AI
• Knowledge Representation and Reasoning in context to Artificial Intelligence
• Expert Systems
• Search Strategies in AI
• Small live Demo of AI application
• Introduction to Explainable AI
• Chat GPT
• Future of AI
• Lab Exercise

Advanced Concepts In AI And ML (2 Weeks)

• Theory of Types of Data
• Exploratory Data Analysis Theory
• Supervised and Unsupervised Learning techniques
• Crash Course of python / Python essentials
• Introduction to the tools like Panda’s profiling and D tale
• Exploratory Data Analysis (Demonstrations)
• Automated features extractions
• Lab Exercise

Applied Machine Learning And Advance Selected Topics (2 Weeks)

• Machine learning Algorithms
• Evaluation of ML project
• Deployment of the Model
• Introduction to Deep learning
• Introduction to reinforcement learning
• Introduction to Model Optimization Techniques
• Artificial Neural Networks
• Lab Exercise

Projects (3 Weeks)

• Sentiment Analysis (theory and practical)
• Image Classification (theory and practical)
• Intelligent Conversational Chatbot (theory and practical)
• Predictive Modelling (Classification and Regression (theory and practical)
• Lab Exercise

*Course content is indicative and subject to the student learning rate.