beginner to advanced – how to become a data scientist

سرفصل های دوره

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

01 - Course introduction

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

002 One important thing before you start.html

003 What are the prerequesits for data science and this course

004 Check you system

005 Download all the source files.html

005 Pokemon.csv

005 Pokemon-Color-Palette.txt

005 baseball.csv

005 matches.csv

005 pima-indians-diabetes.csv

005 sales2.csv

005 test.csv

005 titanicexcel.csv

005 train.csv

005 transit-segments.csv

02 - pandas for data science

001 0 All you need to know about Series

002 1 pandas for data scientists

003 2 pandas for data scientists

004 3 pandas for data scientists

005 4 pandas for data scientists

006 5 Broadcasting operations

007 6 Counting

008 7 The issue with missing values - a common problem in machine learning

009 8 Dealing with missing values 2

010 9 The right data in the right format

011 10 Sorting your data properly

012 11 How to slice your data 1

013 12 How to slice your data 2

014 13 How to check for missing values

015 14 A machine learning insight - a full case study

016 15 Master dates

017 16 How to deal with dublicates

018 17 How to play with the Index

019 18 Slicing techniques

020 19 Slicing techniques 2

021 20 More data science techniques in pandas

022 21 Data querying in pandas

023 22 How to work with dates

024 23 How to work with dates 2

025 24 How to work with dates 3

026 25 How to work with dates 4

027 26 Grouping in pandas beginner to advanced

028 27 The Multiindex

029 28 Data science and Finance

030 29 In depth combining dataframes

031 30 Useful ways to deal with strings (regex example)

032 31 Bonus Tips and Tricks

033 32 Bonus Tips and Tricks 2

034 33 Bonus Tips and Tricks 3

03 - Introduction to numpy - what you need to know

001 34 What are Tensors

002 35 Introduction to numpy 1

003 36 Introduction to numpy 2

004 37 Introduction to numpy 3

005 38 Introduction to numpy 4

04 - Data Visualization

001 39 Matplotlib - a how to guide

002 40 Matplotlib - advanced

003 41 Matplotlib - advanced

05 - Master Data Visualization with Seaborn

001 42 Seaborn introduction

002 43 how to master seaborn 1

003 44 how to master seaborn 2

004 45 how to master seaborn 3

005 46 how to master seaborn 4

006 47 how to master seaborn 5

007 48 how to master seaborn 6

008 49 how to master seaborn 7

009 50 how to master seaborn 8

010 51 how to master seaborn 9

011 52 how to master seaborn 10

012 53 how to master seaborn 11

013 54 how to master seaborn 12

014 55 how to master seaborn 13

015 56 how to master seaborn 14

016 57 The end of the road - What to do now

017 More learning resources for your AI learning journey.html

018 Bonus - How to use Transfer learning to predict ice cream

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

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تولید کننده: Udemy-Training