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Learn Python, R, Neural networks, ANN, Deep learning - DS tools and softwares like knime,spark,scipy, Tableau and others

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Master Data Science, Analytics and become Data Scientist

 

2+

 

What you’ll learn
  • Data science and usage of tools and softwares
 
Requirements
  • Basic computer knowledge is enough.
 
Description
 

Data Science and Data Analytics course covers wide range of topics from language to tools and softwares.

38 videos of around 6 hours duration.

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Section Topic Duration (hh:mm:ss)

 

1.  Data Science

1.1 Data Science introduction 00:09:50

1.2 What is the most powerful language 00:09:36

1.3 Data Science Tools 00:15:46

1.4 Deep Learning 00:14:53

 

2. Python Language

 

1.1 Python – introduction 00:09:55

1.2 Install python on windows 00:04:48

1.4 Understanding Python language 00:10:19

1.5 Python coding style PEP8 00:08:31

2.1 Data types – Strings and numbers 00:10:21

2.2 Comments and docstrings 00:03:43

2.3 Control flow statements 00:08:50

2.4 Data structures – Lists and Tuples 00:11:00

 

3.1 functions 00:11:27

 

3.5 Modules and Packages – I 00:10:08

3.6 Modules and Packages – II 00:08:05

4.1 Python Classes 00:08:54

4.2 Classes – inheritance – multiple inheritance 00:09:47

4.3 Classes – Method Resolution Order (MRO) – multiple inheritance 00:07:33

5.1 File read write IO operations 00:12:03

7.1 Standard libraries 00:05:14

 

3. R Language

1.1 R Lang introduction 00:09:57

1.6 R Lang and Data Science – Tidyverse 00:06:54

1.7 Tidyverse – ggplot2 00:10:45

 

4. KNIME

1.1 KNIME Introduction 00:04:43

1.2 KNIME installation and setup 00:07:12

1.3 KNIME Analytics Platform Practice session 00:15:43

 

5. SciPY

1.1 Scipy introduction 00:10:24

2.1 Numpy introduction 00:06:15

2.2 Numpy – practice session 00:12:36

3.1 Pandas-Python Data Analysis Library 00:06:31

3.2 Pandas- practice session 00:14:29

4.1 Matplotlib – introduction 00:04:38

4.2 Matplotlib – practice session 00:10:15

5.1 Interactive Python – IPython introduction 00:05:06

 

6.1 SymPy 00:08:24

6. Tableau

1.1 Tableau – introduction 00:11:37

1.2 Tableau Desktop public – Practice session 1 00:17:46

1.3 Tableau Desktop public – Practice session WDC 00:06:21

Data Science is evolving science and have appetite for analytics and this course will walk you through the required skills.

 

Who this course is for:
  • Who wants to become data scientist and data analyst

 

Learn Python, R, Neural networks, ANN, Deep learning - DS tools and softwares like knime,spark,scipy, Tableau and others

Data Science, Analytics and become Data Scientist


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