Source: ["The Map of Mathematics" by Domain of Science, Youtube]
Course Overview:
Welcome to Maths and Statistics for AI - Full Course!
This course lays the groundwork for understanding AI by covering essential mathematical concepts. It includes topics like linear algebra, probability, and calculus, which are crucial for data manipulation and model training. Key concepts such as vectors, matrices, probability distributions, and optimization techniques are discussed to build a strong foundation for AI applications.
Chapter 3: Linear Algebra Essentials
Source: ["A friendly introduction to linear algebra for ML (ML Tech Talks)" by TensorFlow, Youtube]
Exercise: - Watch this video and make some notes. Once done, go to the next chapter, Basics of Probability and Statistics.
Chapter 4: Basics of Probability and Statistics
Source: ["Probability And Statistics For Data Science & AI | Probability And Statistics Tutorial | Simplilearn" by Simplilearn, Youtube]
Exercise: - Watch this video and make some notes. Once done, go to the next chapter, Calculus for AI.
Chapter 5: Calculus for AI
Source: ["Calculus - Math for Machine Learning" by Simplilearn, Youtube]
Exercise: 1. Watch this video and make some notes;
2. The next stage is an exam. You have 10 questions, with a total time of 10 minutes. To pass, you need to get 8 out of 10. You can retake it. Once you pass, you will have 1 minute to redeem your certificate by entering your full name correctly!
Exam (Redeem Certificate)
Results
Your score:
Summary
Now you can post your certificate on LinkedIn. You can also explore and learn next AI chapters, other programming languages from Skill-Based Roadmaps or choose a career path from Role-Based Roadmaps.