Intro to AI: A Beginner’s Guide to Artificial Intelligence

سرفصل های دوره

Understand How AI Works and How to Leverage This Technology to Transform Your Business and Career

1 - Getting started

1 - Intro-to-AI-Course-notes.pdf

1 - Natural vs Artificial Intelligence

2 - Brief history of AI

3 - Demystifying AI Data science Machine learning and Deep learning

4 - Weak vs Strong AI

2 - Data is essential for building AI

5 - Structured vs unstructured data

6 - How we collect data

7 - Labelled and unlabelled data

8 - Metadata Data that describes data

3 - Key AI technique

9 - Machine learning

10 - Supervised Unsupervised and Reinforcement learning

11 - Deep learning

4 - Important AI branches

12 - Robotics

13 - Computer vision

14 - Traditional ML

15 - Generative AI

5 - Understanding Generative AI

16 - The rise of Gen AI Introducing ChatGPT

17 - Early approaches to Natural Language Processing NLP

18 - Recent NLP advancements

19 - From Language Models to Large Language Models LLMs

20 - The efficiency of LLM training Supervised vs Semisupervised learning

21 - From NGrams to RNNs to Transformers The Evolution of NLP

22 - Phases in building LLMs

23 - Prompt engineering vs Finetuning vs RAG Techniques for AI optimization

24 - The importance of foundation models

25 - Buy vs Make foundation models vs private models

6 - Practical challenges in Generative AI

26 - Inconsistency and hallucination

27 - Budgeting and API costs

28 - Latency

29 - Running out of data

7 - The AI tech stack

30 - Python programming

31 - Working with APIs

32 - Vector databases

33 - The importance of open source

34 - Hugging Face

35 - Hugging Face

36 - AI evaluation tools

8 - AI job positions

37 - AI strategist

38 - AI developer

39 - AI engineer

9 - Looking ahead

40 - AI ethics

41 - Future of AI

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تولید کننده: Udemy