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1. PYTHON COURSE FOR DATA SCIENCE
DATA ANALYSIS
AND
DATA WRANGLING
BRIDGING DIMENSIONS
CONVERT RAW DATA INTO ACTIONABLE
INSIGHTS
SUPPORTED
BY

2. TOPICS
Why Learn Data
Science
01
How much Data
is Generated?
02 What is the Earning
Potentials?
03
Program Details
05 Trainer and
Mentors
06
Students’ Projects
& Testimonials
07 Fees & Admission
Process
08
MAGES Institute &
MAGES Studio
04

5. HOW MUCH
DATA IS GENERATED?
Data is being created all the time without us even
noticing it. Much of what we do every day now
happens in the digital realm, leaving an ever-
increasing digital trail that can be measured and
analyzed.
Netflix
Subscribers Stream
77,160 Hours
of Video
UBER
Passengers take
694 Rides Facebook
Users Like
4,166,667
Posts
Twitter
Users Send
347,222
Tweets
YouTube
Users Upload
300 Hours of
new video
Instagram
Users Like
1,736,111
Photos
Pinterest
Users Pin
9,722 Images
Apple
Users Download
51,000 Apps
Reddit
Users CAst
18,327 Votes
Amazon
Receives
4,310 Unique
Visitors
Vine
Users Play
1,041,666
Videos
Tinder
Users Swipe
590,278 Times
Snapchat
Users Share
284,722
Snaps
Buzzfeed
Users View
34,150 Videos
Skype
Users Make
110,040 Calls
Every
Minute of
the Day

7. DATA SCIENCE IN VARIOUS INDUSTRIES
Machine Learning
− Data science is leveraged to
disrupt ML based application
Medical
− Disease prediction
− Analyze patient recovery growth
Insurance
− Fraud and risk detection
− Insurance claims prediction
Retail
− Analyze Consumer Behaviors
− Predict Product Pricing
Enterprise
− Capturing data volume, variety
and value
Healthcare
− Detect Causes of disease
− Risk prediction
Digital Marketing
− Detect targeted audience
− Demographic behavior analysis
Funding
− Detect possible fundraisers

8. PROGRAM DETAILS

9. ADVANCED PYTHON FOR DATA
SCIENCE
Assessment
1 Hour
33
Hours
6
Hours
F2F lectures
E-learning
Quizzes and
Exercises

10. MODULES
Data Analysis and Data Wrangling with Python
PRACTICAL OUTCOME BASED ON INDUSTRY
REQUIREMENTS
LU1 – Preparation of Data
Select the best tools and learn the right techniques to wrangle the collected data
Analysis of Data
Evaluate and analyse the data using appropriate tools and techniques based on
business objectives to maximize
Collation and Presentation of Data
Derive insights by performing visual analysis on real world data and articulate how
these insights impact business decisions and lead to improved business objectives

11. TOPICS COVERED
Understanding the Business Domain and
its requirements.
01
Understanding the Dataset - Quality and
Quantity
03
Import data sets
Types of data using tools and
techniques
02
Tools and Techniques for Data Analysis
Importing and Exporting Data in Python
04
Chosen data sets
Clean and prepare data for analysis
05
Manipulate Data Frame
Summarize data
Insights from Data
06

12. LEARNING OUTCOME
Python for Data Science
Select the best tools and learn the right
techniques to wrangle the collected Data.
01
Derive insights by performing visual
analysis on real world DatA.
03
Evaluate and analyse the Data using
appropriate tools and techniques based
on business objectives to maximize
02
Articulate how these insights can
impact/improve business decisions
04

13. TRAINER AND MENTOR

14. THOMAS O’DELL
Adjunct Lecturer in MAGES Institute of
Excellence and Republic Polytechnic B.A
Honours in Computer Science, University of
Toronto, Canada
Thomas significant experience in the IT industry enriches both his industrial
training and his academic teaching
With over 25 years of working experience, in companies such as ICONIX
International and Delcan Corporation in Toronto, Canada.
Vast On-the-Ground Experience
MENTOR | TRAINER

15. STUDENTS’ PROJECTS &
TESTIMOIALS

16. Write a one-page memo describing
your color and format choices and how
you customized this visualization to fit
the needs of your audience
Written Task
 To see the status of the project
 Attempting to see the performance of
the country
 Attempting to see the performance of
the submitting officer
Objectives
To use color to determine the size
of project
Color Selection
Click on the size of the project will be able
to see the submitting officer and the
respective country involved and size of
the total project.
Format Selection

18. The. Majority of Top 100 Universities come from USA,
who has about 8x more top 100 universities than the
next best country: the UK. The difference between the
number of top 100 universities between the UK, Japan,
France, and Switzerland is less drastic compared to
the disparity between USA and UK.
With only integers, it's difficult to see if USA is the best
place to go for a quality education because we should
be using a percentage figure of: (Number of world rank
Top 100 schools / Total Universities in country) *100 to
get a more accurate representation.
Top 5 Countries w Highest numbers of
Top 100 Units

19. THE FUTURE STARTS HERE
PYTHON COURSE IN
DATA WRANGLING
AND ANALYSIS
Thank You for taking the First Step.
Convert raw data into actionable information
SUPPORTED
BY
THANK YOU