Chod Matrix > Development > Data Science > beginner to advanced – how to become a data scientist

4.25 out of 5

41 reviews on Udemy

beginner to advanced – how to become a data scientist

master data science fundamentals for machine learning, deep learning and neural networks

Instructor:

Dan We

909 students enrolled

English [Auto]

You can apply important data science methods on any dataset you want

You have acquired a deep understanding in data exploration and preparation techniques

You understand numpy and it‘s importance for data science

You can apply advanced visualization techniques to present your findings

you are prepared to dive deeper into machine learning and neural networks

You might open up new career opportunities for you which are not only highly rewarding but also offer more job satisfaction

So you want to become a data scientist hm? But you do not know how and where to start?

If your answer to these question is : Yes that’s correct, then you are at the right place!

You could not have chosen a better time to introduce yourself to this topic.Data science is the most interesting topic in the world we live in and beside that also highly rewarding. It will shape our future and therefore it’s better to act now than regret later. Any kind of machine learning (self driving cars, stock market prediction, image recognition, text analyzing or simply getting insights of huge datasets – it’s all part of data science.

The jobs of tomorrow – self employed or employed will encounter exploring, analyzing and visualizing data – it’ s simply the “oil of this century”. And the golden times are yet to come!

“From my personal experience I can tell you that companies will actively searching for you if you aquire some skills in the data science field. Diving into this topic can not only immensly improve your career opportunities but also your job satisfaction!”

With this in mind it’s totally understandable that smart people like you are searching for a way to enter this topic. Most often the biggest problem is how to find the right way master data science from scratch. And that’s what this course is all about.

My goal is to show you and easy, interesting and efficient way to start data science from scratch. Even if you have barely started with coding and only know the basics of python, this course will help you to learn all the relevant skills for data science!

Together let’s learn, explore and apply the core fundamentals in data science for machine learning / deep learning / neural networks and set up the foundation for you future career..

Can’t wait to start coding with you! Meet me in the first lecture!

Best

Daniel

Course introduction

Introduction - Why are you here and what we will accomplish here

One important thing before you start

What are the prerequesits for data science and this course

Check you system

Download all the source files

pandas for data science

0 All you need to know about Series

1 pandas for data scientists

2 pandas for data scientists

3 pandas for data scientists

4 pandas for data scientists

5 Broadcasting operations

6 Counting

7 The issue with missing values - a common problem in machine learning

8 Dealing with missing values 2

9 The right data in the right format

10 Sorting your data properly

11 How to slice your data 1

12 How to slice your data 2

13 How to check for missing values

14 A machine learning insight - a full case study

15 Master dates

16 How to deal with dublicates

17 How to play with the Index

18 Slicing techniques

19 Slicing techniques 2

20 More data science techniques in pandas

21 Data querying in pandas

22 How to work with dates

23 How to work with dates 2

24 How to work with dates 3

25 How to work with dates 4

26 Grouping in pandas beginner to advanced

27 The Multiindex

28 Data science and Finance

29 In depth combining dataframes

30 Useful ways to deal with strings (regex example)

31 Bonus Tips and Tricks

32 Bonus Tips and Tricks 2

33 Bonus Tips and Tricks 3

Introduction to numpy - what you need to know

34 What are Tensors

35 Introduction to numpy 1

36 Introduction to numpy 2

37 Introduction to numpy 3

38 Introduction to numpy 4

Data Visualization

39 Matplotlib - a how to guide

40 Matplotlib - advanced

41 Matplotlib - advanced

Master Data Visualization with Seaborn

42 Seaborn introduction

43 how to master seaborn 1

44 how to master seaborn 2

45 how to master seaborn 3

46 how to master seaborn 4

47 how to master seaborn 5

48 how to master seaborn 6

49 how to master seaborn 7

50 how to master seaborn 8

51 how to master seaborn 9

52 how to master seaborn 10

53 how to master seaborn 11

54 how to master seaborn 12

55 how to master seaborn 13

56 how to master seaborn 14

57 The end of the road - What to do now?

More learning resources for your AI learning journey

Bonus - How to use Transfer learning to predict ice cream

If you like my teaching style and want to continue learning together

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!

4.3

4.3 out of 5

41 Ratings