beginner to advanced – how to become a data scientist
Beginner to Advanced Data Science Skills:
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
pandas for data science
Introduction to numpy - what you need to know
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6
0 All you need to know about Series -
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1 pandas for data scientists
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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
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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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31
25 How to work with dates 4
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32
26 Grouping in pandas beginner to advanced
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33
27 The Multiindex
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28 Data science and Finance
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29 In depth combining dataframes
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30 Useful ways to deal with strings (regex example)
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31 Bonus Tips and Tricks
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32 Bonus Tips and Tricks 2
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33 Bonus Tips and Tricks 3
Data Visualization
Master Data Visualization with Seaborn
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