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

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AI: Data Science, ML, GenAI in Python + ChatGPT, available at $54.99, has an average rating of 4.29, with 87 lectures, 22 quizzes, based on 7 reviews, and has 32 subscribers.

You will learn about Combine the power of Data Science and Machine Learning to create AI for Real-World applications Build different AI applications within projects Master the State of the Art Gen AI models Create own LLM applications How to use Python for Data Science This course is ideal for individuals who are Anyone interested in AI, Data Science, GenAI and Machine Learning or Beginner Python developer curious about Data Science, AI and GenAI or Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning. or Any students in college who want to start a career in Data Science. or Any data analysts who want to level up in Machine Learning. or Any people who are not satisfied with their current job and who want to become a Data Scientist. or Students who have at least high school knowledge in math and who want to start learning Machine Learning. It is particularly useful for Anyone interested in AI, Data Science, GenAI and Machine Learning or Beginner Python developer curious about Data Science, AI and GenAI or Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning. or Any students in college who want to start a career in Data Science. or Any data analysts who want to level up in Machine Learning. or Any people who are not satisfied with their current job and who want to become a Data Scientist. or Students who have at least high school knowledge in math and who want to start learning Machine Learning.

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

Summary

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

Price: $54.99

Average Rating: 4.29

Number of Lectures: 87

Number of Quizzes: 22

Number of Published Lectures: 86

Number of Published Quizzes: 22

Number of Curriculum Items: 109

Number of Published Curriculum Objects: 108

Original Price: €39.99

Quality Status: approved

Status: Live

What You Will Learn

  • Combine the power of Data Science and Machine Learning to create AI for Real-World applications
  • Build different AI applications within projects
  • Master the State of the Art Gen AI models
  • Create own LLM applications
  • How to use Python for Data Science

Who Should Attend

  • Anyone interested in AI, Data Science, GenAI and Machine Learning
  • Beginner Python developer curious about Data Science, AI and GenAI
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Any students in college who want to start a career in Data Science.
  • Any data analysts who want to level up in Machine Learning.
  • Any people who are not satisfied with their current job and who want to become a Data Scientist.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning.

Target Audiences

  • Anyone interested in AI, Data Science, GenAI and Machine Learning
  • Beginner Python developer curious about Data Science, AI and GenAI
  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
  • Any students in college who want to start a career in Data Science.
  • Any data analysts who want to level up in Machine Learning.
  • Any people who are not satisfied with their current job and who want to become a Data Scientist.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning.

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 codewhich 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.

Course Curriculum

Chapter 1: Intro

Lecture 1: Intro

Chapter 2: Artificial Intelligence (AI)

Lecture 1: AI Intro

Lecture 2: AI applications

Lecture 3: GenAI

Lecture 4: Machine Learning

Lecture 5: Deep Learning

Lecture 6: Get presentation here

Chapter 3: Python

Lecture 1: Installing Python

Lecture 2: Setting up Environment

Lecture 3: Our first program

Lecture 4: Classes

Lecture 5: Casting

Lecture 6: Functions

Lecture 7: Operators

Lecture 8: Reshaping Arrays

Lecture 9: Different Data types

Lecture 10: Error handling

Lecture 11: Pandas dataframe

Lecture 12: Get Code here

Chapter 4: Exploratory Data Analysis (EDA)

Lecture 1: Intro

Lecture 2: EDA Part 2

Lecture 3: Get Code here

Chapter 5: GenAI and LLMs – ChatBots

Lecture 1: Create LLM from scratch with own dataset

Lecture 2: LLAMA2 Finetune Chat QA Model

Lecture 3: LLAMA2 Finetune Chat QA Model Part 2

Lecture 4: LLAMA3 finetune model with own dataset

Lecture 5: LLM Gemma model

Lecture 6: LLM hugging face model – LLAMA3

Lecture 7: Train own data with GPT Transformer

Lecture 8: Get Code here

Chapter 6: GenAI and LLM applications

Lecture 1: LLM Langchain Intro

Lecture 2: LLM Langchain Falcon Chatbot

Lecture 3: BERT Finetuned LLM sentiment anaylsis with Fast API

Lecture 4: LLAMA2 GenAI app with Streamlit

Lecture 5: Get code here

Chapter 7: AI Chatbots

Lecture 1: Intro

Lecture 2: Use AI Chatbots locally

Lecture 3: Advanced Data Analysis with Gemini

Chapter 8: Machine Learning

Lecture 1: Intro

Lecture 2: Time series Random Forest – stock prediction

Lecture 3: Time series XGBoost – stock prediction

Lecture 4: Get code here

Chapter 9: Deep Learning

Lecture 1: Intro

Lecture 2: Stock price prediction with LSTM

Lecture 3: Neural Networks cancer data classification

Lecture 4: Handwritten data prediction with CNN – classification

Lecture 5: Get code here

Chapter 10: ETL and SQL

Lecture 1: Mito ETL application

Lecture 2: SQL & pandas – insert data into database

Lecture 3: SQL with sqlalchemy – insert data into database

Chapter 11: Anomaly Detection and Predictive Maintenance

Lecture 1: Anomaly detection with ARIMA – time series

Lecture 2: Anomaly detection with Spectral Residual- time series

Lecture 3: Anomaly detection with XGBoost- time series

Lecture 4: Anomaly detection and decomposition with Spectral Residual – time series

Lecture 5: Get code here

Chapter 12: Web Crawler

Lecture 1: Web crawler Intro

Lecture 2: Web crawler – Firecrawl

Lecture 3: Web crawler – Firecrawl Part 2

Lecture 4: Web scraping- Amazon

Lecture 5: Web scraping- Amazon Part 2

Lecture 6: Get code here

Chapter 13: Image generation with Dall-E

Lecture 1: Image generation with Dall-E

Lecture 2: Image generation with Copilot

Chapter 14: Interfaces (REST API)

Lecture 1: REST API with Flask

Lecture 2: REST API with Weclapp request

Lecture 3: REST API with FastAPI

Lecture 4: Get code here

Instructors

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Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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