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This is data science course for beginners. Its a 1 hour of crash course and it covers the below topics
00:00 Introduction
2:02 Chapter 1:- The main goal :- Artificial intelligence
3:06 Chapter 2:- Human attempts for implementing AI
4:23 Chapter 3:- Machine Learning - Self learning
6:41 Chapter 4:- TAMA Machine learning life cycle.
8:21 Chapter 5:- Data science - Multi-disciplinary field.
9:50 Chapter 6:- Implementing Linear regression using excel.(Lab 1)
15:07 Chapter 7:- Summarizing what data science constitutes.
16:46 Chapter 8:- Supervised VS non-supervised learning
20:18 Chapter 9:- implementing non-supervised learning using excel (Lab2)
30:31 Chapter 10:- Data mining
30:58 Chapter 11:- Deep learning and neural networks
32:55 Chapter 12:- Summarizing AI,ML and DS space.
36:47 Chapter 13:- Why python is preferred for AI,ML and DS ?
40:00 Chapter 14:- Installation of python framework and pycharm IDE
44:26 Chapter 15:- Implementing Linear regression using python and scipy (Lab3)
Chapter 16:- Installation of R framework and R studio
Chapter 17:- Implementing Linear regression using R programming (Lab4)
Chapter 18:- Installation of python framework and pycharm IDE
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