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Angel Hill
- Rate R501
- Response 1h
-
Students2
Number of students Angel Hill has accompanied since joining Superprof
Number of students Angel Hill has accompanied since joining Superprof
R501/h
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- Artificial Intelligence
Introduction to AI, Predictive and Generative Artificial Intelligence, LLMs (Large Language Models), and Their Practical Applications
- Artificial Intelligence
Lesson location
About Angel Hill
I am a freshly graduated undergrad student with considerable experience inside and outside the classroom with data science and building AI and machine learning models. I am early on in my full time career (in the data science space) and do tutoring on the side to make extra income.
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About the lesson
- Primary
- Secondary
- Matric/GCSE
- +12
levels :
Primary
Secondary
Matric/GCSE
AS Level
A Level
BTech
Adult education
Masters
Doctorate
MBA
Beginner
Intermediate
Advanced
Professional
Kids
- English
Languages in which the lesson is available :
English
- Lessons taught by experienced data scientist with excellent communication and technical skills.
- Lessons are very in depth, but also easy to understand. You'll be an AI expert by the end of the course!
- Lesson plan is tailored to how and what you want to learn.
- Can include more conceptual material, or more programming and technical material.
- Lessons on building your own AI models in Python and R also available. I can make them as in depth as needed.
- Example course plan below:
1. Concepts of AI and machine learning
- breakdown of how AI models function on a technical level
- no programming yet
2. Use Cases of AI
- explanation of basic applied AI models
- staying up to date with AI news
3. In Depth Applied AI
- technical breakdown of advanced machine learning algorithms
- intro to LLMs
4. Breakdown of LLMs and Use Cases
- further breakdown of LLMs (ChatGPT) and how they process data
- pretrained vs fine tuned LLMs
5. Data Preparation for AI and Machine Learning
- technical walkthrough of how data is sourced and prepared to train AI algorithms (this is the MOST important part of AI & ML)
6. AI and Statistics
- walkthrough of AI statistical learning
7. Intro to Programming for AI
- intro to Python (and other tools / languages) for building AI models
- no programming (yet)
8. Intro to Python I
- IDE setup
- variables, functions, print statements
9. Intro to Python II
- Python fundamentals (user defined functions, data types, etc)
10. Intro to Python III
- if statement and loops
11. Intro to Data Types
12. Debugging
13. Advanced Data Types
14. Algorithm Design
- data processing and data flow for Python algorithms
15. Python packages and extensions
- using libraries and packages
16. Using AI to build AI tools
- using ChatGPT, Bard, and Copilot for Python and machine learning
- ChatGPT for debugging
- AI ethics (more important than you think)
17-20. Data Analysis with Python (if needed)
- analyze and process data using pandas, numpy, etc (Python packages) to be used to train AI model
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Rates
Rate
- R501
Package rates
- 5h: R2505
- 10h: R5010
online
- R501/h
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