Data Science & Machine Learning : Hands on Data Science 2020
4.3 (394 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
7,435 students enrolled

Data Science & Machine Learning : Hands on Data Science 2020

Numpy, Pandas, Matplotlib, Scikit-Learn, WebScraping, Data Science, Machine Learning, Pyspark, statistics, Data Science
4.3 (394 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
7,435 students enrolled
Last updated 3/2020
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Current price: $64.99 Original price: $99.99 Discount: 35% off
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This course includes
  • 15.5 hours on-demand video
  • 19 articles
  • 21 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Assignments
  • Certificate of Completion
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What you'll learn
  • You will Learn one of the most in demand skill of 21st century Data Science
  • Add Data science skills : python, numpy, pandas, plotly, tableau, machine learning, statistics, probability in your resume
  • Apply linear regression and logistics regression on real dataset.
  • Crash course on python
  • Apply matrix operation with Numpy - Numerical python library
  • Visualize your data with mother of all visualisation library available in Python : MatplotLIb
  • Perform Data analysis, wrangling and cleaning with pandas library
  • Get hands on with interactive visualisation library Plotly
  • Getting start with data visualization tool, Tableau
  • Data Pre-processing technique - Missing data, Normalization, one hot encoding,
  • Importing data in Python from different sources, Files
  • Web Scraping to download web page and extract data
  • Data scaling and transformation
  • Exploratory Data analysis
  • Feature engineering process in Machine Learning system design
  • Machine learning theory
  • Apache spark installation : pyspark
  • Getting started with spark session
  • Mathey required for machine learning : Statistics, probability
  • Setup Data Science Virtual machine on Microsoft Azure Cloud
Course content
Expand all 152 lectures 15:32:31
+ Introduction
5 lectures 18:26
Overview Of Jupyter Notebook
05:25
Notes About Course
03:24
Join Online Classroom
00:14
Introduction
2 questions
+ Python crash course
6 lectures 50:29
Introduction - Python
01:40
Python - Number, String, Variable
11:41
Python - List, tuples, Dictionary, Set
12:46
Python - If/else, Looping
10:47
Python - Function, Lambda, Map
13:03
Python
11 questions
Python Exercise
00:32
Python Assignment
Scrap Google home page title.
1 question
+ Data analysis with Numpy
5 lectures 33:58
Introduction - Numpy - Numerica Python
03:15
Numpy array operations
06:14
Indexing, Slicing - Numpy array
10:09
Quiz
6 questions
Numpy Exercise
00:14
+ Data analysis with Pandas
8 lectures 01:00:56
Introduction - Pandas
02:32
Pandas - Introduction to Series
07:01
Dataframe - Index, Multiindex
08:38
Handling Missing Data - dropna, fillna
07:52
Grouping data
10:37
Read, Write .csv, .html, excel file
05:20
Visualization of data with pandas
07:27
+ Data Visulization with Matplotlib
5 lectures 20:44
Introduction
02:53
Why Visualization ?
00:27
MatplotLib - Basic plotting, Plotting terminology
09:40
MatplotLib - Subplots
04:12
Matplotlib - Special plot
03:32
Matplotlib
8 questions
+ Data visualization - plotly
8 lectures 41:10
Plotly - introduction
03:01
Basic plotting - plotly
08:00
Exercise : Extend Basic Plot
00:08
Plotly - Bar chart
04:09
Exercise : Extend Bar Chart
00:09
Plotly - Bubble chart
03:28
Plotly - Histogram and Distribution plot
11:48
Plotly
1 question
+ Data visualization with Tableau
5 lectures 36:44
Introduction to Tableau and Installation
07:06
Load Data in Tableau
04:50
Insight -1
12:30
Save Tableau Worksheet
03:08
+ Introduction to Data
2 lectures 17:30
Introduction to Data, Continuous and Discrete Data
08:56
Nominal and Ordinal Data
08:34
Identify Types of Data
6 questions
+ Importing Data in python
7 lectures 37:46
Introduction
01:47
Reading Plain text file
04:39
Reading .csv file
07:24
Reading Excel and .m Matlab file
04:05
Read Sqlite Database
03:52
Fetch Data from Remote file
06:50
+ Data Preprocessing
6 lectures 38:33
Reading Data
05:17
Handling Missing Data
08:44
Splitting Data in Training and Testing Set
03:49
Normalize Data
07:38
Requirements
  • Basic of Python programming
  • High school mathematics
Description

Welcome to Complete Ultimate course guide on Data Science and Machine learning with Python.

Have you ever thought about

How amazon gives you product recommendation, 

How Netflix and YouTube decides which movie or video you should watch next,

Google translate translate one language to another,

How Google knows what is there in your photo,

How  Android speech Recognition or Apple siri understand your speech signal with such high accuracy.

If you would like algorithm or technology running behind that,  This is first course to get started in this direction.

==============================================

This course has more than 100 - 5 star rating.

What previous students have said: 

"This is a truly great course! It covers far more than it's written in its name: many data science libraries, frameworks, techniques, tips, starting from basics to advanced level topics. Thanks a lot!  "

"This course has taught me many things I wanted to know about pandas. It covers everything since the installation steps, so it is very good for anyone willing to learn about data analysis in python /jupyter environment."

"learning valuable concepts and feeling great.Thanks for this course."

"Good explanation, I have laready used two online tutorials on data -science and this one is more step by step, but it is good"

"i have studied python from other sources as well but here i found it more basic and easy to grab especially for the beginners. I can say its best course till now . it can be improved by including some more examples and real life data but overall i would suggest every beginner to have this course."

"The instructor is so good, he helps you in all doubts within an average replying time of one hour. The content of the course and the way he delivers is great."

==================================================

Why Data Science Now?

Data Scientist: The Sexiest Job of the 21st Century - By Harvard Business review

There is huge sortage of data scientist currently software industry is facing.

The average data scientist today earns $130,000 a year  by  glassdoor.

Want to join me for your journey towards becoming Data Scientist, Machine Learning Engineer.

This course has more than 100+ HD -  quality video lectures and is over 13+ hours in content.

This is first introductory course to get started data analysis, Machine learning and towards  AI algorithm implementation

This course will teach you - All Basic python library required for data analysis process.

  • Python  crash course

  • Numerical Python - Numpy

  • Pandas - data analysis

  • Matplotlib for data visualization

  • Plotly and Business intelligence tool Tableau

  • Importing Data in Python from different sources like .csv, .tsv, .json, .html, web rest Facebook API

  • Data Pre-Processing like normalization, train test split, Handling missing data 

  • Web Scraping with python BeautifulSoup - extract  value from structured HTML Data

  • Exploratory data analysis on pima Indian diabetes dataset

  • Visualization of Pima Indian diabetes dataset

  • Data transformation and Scaling Data -  Rescale Data, Standardize Data, Binarize Data, normalise data

  • Basic introduction to What is Machine Learning, and  Scikit learn overview Its type, and comparison with traditional system. Supervised learning vs Unsupervised Learning

  • Understanding of regression, classification and clustering

  • Feature selection and feature elimination technique.

  • And Many Machine learning algorithm yet to come. 

  • Data Science Prerequisite : Basics of Probability and statistics

  • Setup Data Science and Machine learning lab in Microsoft Azure Cloud

This course is for beginner and some experienced programmer who want to make career in Data Science and  Machine learning, AI.

Prerequisite:

  • basic knowledge in python programming (will be covered in python )

  • High School mathematics

Enroll in this course, take look at brief curriculum of this course and take first step in wonderful world of Data.

See you in field.

Sincerely,

Ankit Mistry


Who this course is for:
  • Anyone who is interested in DataScience
  • Anyone who wants to learn - How to analyze data
  • Those who want to make career in Data analytics, Machine learning, DataScience