beginner to advanced - how to become a data scientist
5.0 (2 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
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beginner to advanced - how to become a data scientist

master data science fundamentals for machine learning, deep learning and neural networks
New
5.0 (2 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
45 students enrolled
Created by Daniel We
Last updated 9/2017
English
English [Auto-generated]
Current price: $10 Original price: $200 Discount: 95% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 10 hours on-demand video
  • 1 Article
  • 9 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • 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
View Curriculum
Requirements
  • Basic knowledge in python is helpful
  • Your personal interest, commitment and >10h of your time
  • An open mindset
Description

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!

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

Who is the target audience?
  • beginners with no prior knowlege
  • beginners who have acquired some knowledge
  • students who are interested in a data science career
  • students who want to acquire a solid foundation to dive into machine learning and neural networks
Compare to Other Data Science Courses
Curriculum For This Course
62 Lectures
10:10:12
+
Course introduction
4 Lectures 09:09

What are the prerequesits for data science and this course
02:14

Check you system
05:10

Download all the source files
00:05
+
pandas for data science
34 Lectures 06:35:05



3 pandas for data scientists
06:21

4 pandas for data scientists
08:47

5 Broadcasting operations
07:11

6 Counting
05:52

7 The issue with missing values - a common problem in machine learning
10:44

8 Dealing with missing values 2
10:55

9 The right data in the right format
06:06

10 Sorting your data properly
06:18

11 How to slice your data 1
06:22

12 How to slice your data 2
05:09

13 How to check for missing values
04:35

14 A machine learning insight - a full case study
25:15

15 Master dates
11:58

16 How to deal with dublicates
06:03

17 How to play with the Index
07:39

18 Slicing techniques
11:19

19 Slicing techniques 2
21:50

20 More data science techniques in pandas
11:51

21 Data querying in pandas
06:42

22 How to work with dates
26:17

23 How to work with dates 2
03:35

24 How to work with dates 3
05:03

25 How to work with dates 4
03:35

26 Grouping in pandas beginner to advanced
17:59

27 The Multiindex
19:40

28 Data science and Finance
26:22

29 In depth combining dataframes
31:18

30 Useful ways to deal with strings (regex example)
15:39

31 Bonus Tips and Tricks
09:04

32 Bonus Tips and Tricks 2
07:08

33 Bonus Tips and Tricks 3
11:47
+
Introduction to numpy - what you need to know
5 Lectures 48:02
34 What are Tensors
08:24

35 Introduction to numpy 1
06:42

36 Introduction to numpy 2
10:26

37 Introduction to numpy 3
09:55

38 Introduction to numpy 4
12:35
+
Data Visualization
3 Lectures 01:30:40
39 Matplotlib - a how to guide
25:26

40 Matplotlib - advanced
28:08

41 Matplotlib - advanced
37:06
+
Master Data Visualization with Seaborn
16 Lectures 01:07:15
42 Seaborn introduction
01:33

43 how to master seaborn 1
05:28

44 how to master seaborn 2
05:07

45 how to master seaborn 3
05:34

46 how to master seaborn 4
03:38

47 how to master seaborn 5
05:05

48 how to master seaborn 6
06:47

49 how to master seaborn 7
03:21

50 how to master seaborn 8
05:27

51 how to master seaborn 9
05:24

52 how to master seaborn 10
06:53

53 how to master seaborn 11
02:13

54 how to master seaborn 12
02:22

55 how to master seaborn 13
03:43

56 how to master seaborn 14
03:37

57 The end of the road - What to do now?
01:03
About the Instructor
Daniel We
4.5 Average rating
235 Reviews
5,873 Students
21 Courses
Traveller

Daniel is a 28 year old entrepreneur ,data scientist and web analyst consultant. He holds a master degree as well as other major certificates from Google and others.

He is committed to support other people by offering them educational services to help them accomplishing their goals and becomming the best in their profession.

"In order to do the impossible you need to see the invisible"