4.25 out of 5
4.25
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
907 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 itβ€˜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,Β 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.Β Any kind of machine learningΒ (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 visualizingΒ 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 likeΒ you are searching for a way to enter this topic. Most often the biggest problem isΒ 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 Β python, this course will help you to learn all the relevant skills for data science!

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

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

BestΒ 

Daniel

Course introduction

1
Introduction - Why are you here and what we will accomplish here
2
One important thing before you start
3
What are the prerequesits for data science and this course
4
Check you system
5
Download all the source files

pandas for data science

1
0 All you need to know about Series
2
1 pandas for data scientists
3
2 pandas for data scientists
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3 pandas for data scientists
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4 pandas for data scientists
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5 Broadcasting operations
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6 Counting
8
7 The issue with missing values - a common problem in machine learning
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8 Dealing with missing values 2
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9 The right data in the right format
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10 Sorting your data properly
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11 How to slice your data 1
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12 How to slice your data 2
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13 How to check for missing values
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14 A machine learning insight - a full case study
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15 Master dates
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16 How to deal with dublicates
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17 How to play with the Index
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18 Slicing techniques
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19 Slicing techniques 2
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20 More data science techniques in pandas
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21 Data querying in pandas
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22 How to work with dates
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23 How to work with dates 2
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24 How to work with dates 3
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25 How to work with dates 4
27
26 Grouping in pandas beginner to advanced
28
27 The Multiindex
29
28 Data science and Finance
30
29 In depth combining dataframes
31
30 Useful ways to deal with strings (regex example)
32
31 Bonus Tips and Tricks
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32 Bonus Tips and Tricks 2
34
33 Bonus Tips and Tricks 3

Introduction to numpy - what you need to know

1
34 What are Tensors
2
35 Introduction to numpy 1
3
36 Introduction to numpy 2
4
37 Introduction to numpy 3
5
38 Introduction to numpy 4

Data Visualization

1
39 Matplotlib - a how to guide
2
40 Matplotlib - advanced
3
41 Matplotlib - advanced

Master Data Visualization with Seaborn

1
42 Seaborn introduction
2
43 how to master seaborn 1
3
44 how to master seaborn 2
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45 how to master seaborn 3
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46 how to master seaborn 4
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47 how to master seaborn 5
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48 how to master seaborn 6
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49 how to master seaborn 7
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50 how to master seaborn 8
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51 how to master seaborn 9
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52 how to master seaborn 10
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53 how to master seaborn 11
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54 how to master seaborn 12
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55 how to master seaborn 13
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56 how to master seaborn 14
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57 The end of the road - What to do now?
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More learning resources for your AI learning journey
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Bonus - How to use Transfer learning to predict ice cream
19
If you like my teaching style and want to continue learning together
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Includes

10 hours on-demand video
4 articles
Full lifetime access
Access on mobile and TV
Certificate of Completion