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Data Science 101: Methodology, Python, and Essential Math

You're reading from Data Science 101: Methodology, Python, and Essential Math A beginner's guide to data science, starting from data science methodology to an introduction to data science in Python, to essential math for data science.

Product type Video

Published in Apr 2022

Publisher Packt

ISBN-13 9781803242125

Length 14hrs 49mins

Edition 1st Edition

Languages

Python

Concepts

Data Science

Author (1):

Ermin Dedic

View More author details

Table of Contents (19) Chapters

1. Introduction to Data Science 101 FREE CHAPTER

2. Best Language for Data Science

3. Data Science Methodology

4. Data Science Through Chatbot

5. Libraries, APIs, Datasets

6. GitHub

7. Installation / Jupyter / Comments (Windows and MacOS/Jupyter Notebook)

8. Introduction to Data Science in Python - Python Fundamentals

9. Introduction to Data Science in Python - Decision and Looping Structures

10. Introduction to Data Science in Python - Python Functions

11. Introduction to Data Science - Nested Data, Iteration, and List Comprehension

12. Introduction to Data Science in Python - Learn NumPy

13. Introduction to Data Science in Python - Pandas

14. Introduction to Data Science in Python - Python Activity Solutions

15. Essential Math for Data Science - Linear Algebra Made Easy

16. Essential Math for Data Science - Mathematical Structures

17. Essential Math for Data Science - Introduction to Probability

18. Essential Math for Data Science - Random Variables and Multiple Variables

19. Essential Math for Data Science - Statistical Inference

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Data Science 101: Methodology, Python, and Essential Math [Video]

Published in: Apr 2022

Publisher: Packt

ISBN-13: 9781803242125

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Authors (1)

Ermin Dedic

Ermin Dedic

Ermin Dedic started his studies by studying psychology for six years. He received his bachelor's degree from the University of Ottawa, Canada, and his master's degree from the University of Calgary, Canada. Ermin also spent two years in a master's program (school/child psychology) at the University of Calgary before voluntarily withdrawing, in part to focus more on his teaching. It was through academia that he was introduced to and fell in love with statistics and statistical programming with SAS. He is passionate about making education accessible and fun for students. Ermin believes that students learn better when they feel the passion that the instructor has for the content.

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