Data Science - Master Analytics and become Data Scientist

Course details

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

49 videos of around 8 hours duration.

SectionTopicDuration (hh:mm:ss)

1.  Data Science

1.1 Data Science introduction00:09:50

1.2 What is the most powerful language00:09:36

1.3 Data Science Tools00:15:46

1.4 Deep Learning00:14:53

2. Python Language

1.1 Python - introduction00:09:55

1.2 Install python on windows00:04:48

1.4 Understanding Python language00:10:19

1.5 Python coding style PEP800:08:31

2.1 Data types - Strings and numbers00:10:21

2.2 Comments and docstrings00:03:43

2.3 Control flow statements00:08:50

2.4 Data structures - Lists and Tuples00:11:00

3.1 functions00:11:27

3.5 Modules and Packages - I00:10:08

3.6 Modules and Packages - II00:08:05

4.1 Python Classes00:08:54

4.2 Classes - inheritance - multiple inheritance00:09:47

4.3 Classes - Method Resolution Order (MRO) - multiple inheritance00:07:33

5.1 File read write IO operations00:12:03

7.1 Standard libraries00:05:14

3. R Language

1.1 R Lang introduction00:09:57

1.2 Installation of R and R Studio00:14:46

2.1 R Language Intro, Vectors and Objects00:13:33

2.2 R Language Objects factors00:04:41

2.3 R Language Arrays Matrices00:12:57

2.4 R Language Lists - Data frames00:10:35

2.5 R Language File IO - reading from and writing to files00:15:20

2.6 R Language Control flow statements

2.7 R Language Functions

2.8 R Language Statistics, Probability distributions00:11:33

2.9 R Language Packages - Create, build, install and package00:13:47

2.10 R Language Plots

2.11 RLang and DataScience - Tidyverse00:06:54

2.12 Tidyverse - ggplot200:10:45

3.1 R Language secrets

4. KNIME

1.1 KNIME Introduction00:04:43

1.2 KNIME installation and setup00:07:12

1.3 KNIME Analytics Platform Practice session00:15:43

5. SciPY

1.1 Scipy introduction00:10:24

2.1 Numpy introduction00:06:15

2.2 Numpy - practice session00:12:36

3.1 Pandas-Python Data Analysis Library00:06:31

3.2 Pandas- practice session00:14:29

4.1 Matplotlib - introduction00:04:38

4.2 Matplotlib - practice session00:10:15

5.1 Interactive Python - IPython introduction00:05:06

6.1 SymPy00:08:24

6. Tableau

1.1 Tableau - introduction00:11:37

1.2 Tableau Desktop public - Practice session 100:17:46

1.3 Tableau Desktop public - Practice session WDC00:06:21

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