Data Science – Master Analytics and become Data Scientist

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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 00:14:532. 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 00:05:143. R Language 1.1 R Lang introduction 00:09:571.2 Installation of R and R Studio 00:14:462.1 R Language – Intro, Vectors and Objects 00:13:332.2 R Language -Objects factors 00:04:412.3 R Language – Arrays Matrices 00:12:572.4 R Language – Lists – Data frames 00:10:352.5 R Language – File IO – reading from and writing to files 00:15:202.6 R Language – Control flow statements 2.7 R Language – Functions 2.8 R Language – Statistics, Probability distributions 00:11:332.9 R Language – Packages – Create, build, install and package 00:13:472.10 R Language – Plots 2.11 RLang and Data Science – Tidyverse 00:06:542.12 Tidyverse – ggplot2 00:10:453.1 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 00:15:435. Sci PY 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 Sym Py 00:08:246. 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 00:06:21Data Science is evolving science and have appetite for analytics and this course will walk you through the required skills.