Data Science remains to be the need of the hour and shows no signs of slowing down. Data Science platforms are deployed for sustainability in highly competitive industries enabling optimal use of analytics. As the world produces exponentially more data as time passes, so does the need to collect/gather, wrangle/arrange and analyse the data collected.

1. THE FUTURE STARTS HERE
ADVANCED
PYTHON COURSE
FOR DATA SCIENCE
BRIDGING DIMENSIONS
ADVANCED DATA ANALYSIS AND WRANGLING WITH
PYTHON
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. WHY LEARN DATA SCIENCE?
• The demand for data science professionals is at an all-time high, and the
supply hasn’t been able to catch up, leading to an acute shortage of talent
• As more and more companies move to the cloud, the need for data science
and engineering talent will further increase
• Rapid growth and demand in digital transformation and advanced
analytics have led to a surge in demand for data science professionals in
key technology areas such as artificial intelligence

8. 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

10. DATA SCIENCE
IN DEMAND

11. 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

12. Data Science Career
Path

13. PROGRAM DETAILS

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

15. 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

16. 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

17. LEARNING OUTCOME
Data Analysis and Wrangling with Python
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

18. 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

20. 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

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