AI: Data Science, ML, GenAI in Python + ChatGPT

Interested in the field of AI, Data Science, GenAI and Machine Learning?

Then this course is for you!

This course has been designed by an AI, Data Scientist, and a Machine Learning expert so that i can share my knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.

I will walk you step-by-step into the World of AI, Data Scientist, Machine Learning and GenAI. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, and at the same time, we dive deep into AI, Machine Learning and GenAI.

It is structured the following way:

• Part 1 - Intro

• Part 2 - AI

• Part 3 – Python

• Part 4 - EDA

• Part 5 - GenAI Chatbots

• Part 6 - GenAI applications

• Part 7 - AI Chatbots

• Part 8 - Machine Learning

• Part 9 - Deep Learning

• Part 10 - ETL and SQL

• Part 11 - Anomaly Detection (Predictive Maintenance)

• Part 12- Web Crawling & Scraping

• Part 13 - Image generation

• Part 14 - Interfaces REST API

• Part 15 - AI Agents

• Part 16 - Video generation

• Part 17 - ChatGPT-Data Analysis

• Part 18 - ChatGPT-Developing

• Part 19- Pinecone Vector Database

• Part 20 - Web-Apps

• Part 21 - PDF analysis

Each section inside each part is independent. So you can either take the whole course from start to finish or you can jump right into any specific section and learn what you need for your career right now.

Moreover, the course is packed with practical exercises that are based on real-life case projects. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models and applications.

And last but not least, this course includes Python code which you can download and use on your own projects.

What you’ll learn

• Master Machine and Deep Learning on Python

• Have a great intuition of many Machine Learning models 

• Build own GenAI applications

• Use and finetune LLM models

• Make powerful analysis

• Use Machine Learning for personal purpose

• Handle specific topics like Reinforcement Learning, NLP and Deep Learning

• Handle advanced techniques like Dimensionality Reduction

• Know which Machine Learning and LLM model to choose for each type of problem

• Build an army of powerful Machine and Deep Learning models and know how to combine them to solve any problem

Are there any course requirements or prerequisites?

• Just some high school mathematics level and basic programming understanding.