Data Science – Master Analytics and become Data Scientist

Data Science – Master Analytics and become Data Scientist

**More information:

Get Data Science – Master Analytics and become Data Scientist at Salaedu.com

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Description

Learn Python, RLang, Neural networks, ANN, Deep learning – Tools, softwares like knime,spark,scipy, Tableau and others.

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.

49 videos of around 8 hours duration.

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

1.2 Installation of R and R Studio 00:14:46

2.1 R Language – Intro, Vectors and Objects 00:13:33

2.2 R Language -Objects factors 00:04:41

2.3 R Language – Arrays Matrices 00:12:57

2.4 R Language – Lists – Data frames 00:10:35

2.5 R Language – File IO – reading from and writing to files 00:15:20

2.6 R Language – Control flow statements

2.7 R Language – Functions

2.8 R Language – Statistics, Probability distributions 00:11:33

2.9 R Language – Packages – Create, build, install and package 00:13:47

2.10 R Language – Plots

2.11 RLang and DataScience – Tidyverse 00:06:54

2.12 Tidyverse – ggplot2 00:10:45

3.1 R Language secrets

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

Self Help – Self Help online course

More information about Self Help:

Self-help or self-improvement is a self-guided improvementóeconomically, intellectually, or emotionallyóoften with a substantial psychological basis.
Many different self-help group programs exist, each with its own focus, techniques, associated beliefs, proponents and in some cases, leaders.
Concepts and terms originating in self-help culture and Twelve-Step culture, such as recovery, dysfunctional families, and codependency have become firmly integrated in mainstream language.

Self-help often utilizes publicly available information or support groups, on the Internet as well as in person, where people in similar situations join together.
From early examples in self-driven legal practice and home-spun advice, the connotations of the word have spread and often apply particularly to education, business,
psychology and psychotherapy, commonly distributed through the popular genre of self-help books.
According to the APA Dictionary of Psychology, potential benefits of self-help groups that professionals may not be able to provide include friendship,
emotional support, experiential knowledge, identity, meaningful roles, and a sense of

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