PG in Data Science


About PGD in Data Science

Digital transactions and digital interactions are generating a large volume of data. Businesses, Governments and almost everyone else is using Data Science to generate insights by uncovering patterns and by decoding this data. These insights are helping to improve efficiency and to offer newer and better services. It’s even helping political parties to win elections.

So what is Data Science? Data science is a blend of interdisciplinary fields like statistics, data management and technology which can be applied to almost every domain or industry. Data Science has evolved with the advent of machine learning, artificial intelligence and through availability of sophisticated tools for data analysis. 

Why has Data Science suddenly become a buzz word? When all enabling factors are in place, things happen and that is what is happening in Data Science now:
-   Data is available in abundance
-   Technology and tools have matured
-   It can be used by every industry from medical to finance to logistics

Here’s why Data Science is the hottest career option today -

●   Analytics industry is growing at an unprecedented rate, and is witnessing a multifold increase in the number of jobs. The demand in the job market across India has currently surged to 32.2% (Source: The Times of India). 
●   Shortage of Skills: There would be an estimated shortage of almost 2 lakh analytics professionals in the year 2018. Moreover, there would be an increase in the overall pay scale for the analytics professionals. (Source: Indian Express)
●   Lucrative pay packages: Data Scientists with 5+ years of experience are earning more than CAs and Engineers (Source: The Times of India).
●   Competitive Advantage: Be it Finance, Marketing or Engineering Professionals, knowledge of Analytics can help you to keep up with the changes and stay ahead of the pack.
●   Glassdoor has named analytics as the best job of 2016 (Source: The Hindu)


Unique aspects of the Course

●   Comprehensive coverage on various analytical tools like R, SAS, Hadoop, Python, etc.
●   Advanced Analytics: Learn Text Analytics, Machine Learning and Advanced Marketing Analytics.
●   Online Material: 24 * 7 access to practice material, videos, quizzes, mock tests, etc., to ensure learning efficiency.
●   Application across various sectors: like logistics, HR government, e-commerce, finance, marketing, retail, media, etc.
●   Expert faculty with wide industry experience in the analytics industry and alumni of top universities.
●   Flexible learning options: Flexibility for working professionals and students with weekend batches and online learning options that saves you from taking a sabbatical. 
●   Capstone Project: A unique learning opportunity to work on a real-life business case and perform data cleaning and analysis tasks. The project will be mentored and evaluated by an industry expert.
●   Start-up Projects: Student enrolling for the Data Science Plus course will get an access to additional live projects from start-ups.
●   Placement assistance: Candidates will receive 100% placement assistance which includes interview grooming, group discussions, resume writing etc.

Eligibility Criteria

-   Graduation in any stream with at least 60% in 12th standard
-   Third and final year students can join the program. However they can earn the PG Diploma certificate only after successfully completing their bachelor’s degree.

Fee: INR 85,000 + GST

Course Outline

Proschool has divided the course into 3 parts
a. Business Analytics 
b. Big data Tools  & Technology 
c. Advance Analytics

a.  Business Analytics
SubjectContent
Basic Statistical Concepts
Data Summarization and Representation
Measures of Central Tendency and Dispersion
Probability Concepts
Probability Distributions – Normal distribution
Sampling and Estimation
Hypothesis Testing
Excel Proficiency
Formatting of Excel Sheets
Use of Excel Formulae Function
Advanced Modeling Techniques
Data Filter and Sort
Charts and Graphs
Table formula and Scenario building
lookups, pivot tables
Introduction to macros
Predictive Analytics
Simple & Multilinear Regression
Coefficient of Determination & Adjusted R2
Building Regression Model
Interpretation of Coefficients, Dummy Variables
Residual Analysis, Outliers
Logistic Regression -  Assumptions, Model Building, Logistic function
Interpreting coefficients, Model Accuracy
HosmerLemeshow test, Kolmogorov Smirnov Statistic and Chart
Predictive Analytics: Forecasting 
Principles of Forecasting
Concept if Time Series, Causal Models
Types of Forecasting Methods – Exponential Smoothening, Moving Average
Trend, Seasonality, Cyclicity
Holt-Winter’s Forecasting Method
Data Mining Techniques: Market Basket Analysis 
Basic Concepts
Frequent Item set Mining Methods
Apriori, FP growth
Pattern Evaluation Methods – Lift, Support
Data Mining Techniques: Classification
Concept of Classification
Decision Tree Induction
Bayes Method, Rule-Based Classification
Ensemble Approaches
Data Mining Techniques: Clustering
Concept of Clustering
Partitioning Methods, Hierarchical Methods
Density Based Method, Grid Based Method
Kmeans Method
Evaluation of Clustering
Application of Concepts in R and SAS
Reading & Writing the data in R
R- Vectors, Frames, Subsets
Code writing, R code debugger
Reading, Managing and Manipulating data in SAS
Creating Charts in SAS
Application of Predictive and Data Mining Techniques in R and SAS
b. Big Data Tools and Technology 
SQL - Database
Introduction to Databases – Terminologies: Records, Fields, Tables
Introduction to Database Normalization, Primary key, Accessing the data
Introduction to SQL – syntax, data types, operators, Table creation in SQL
Table Access and Manipulation – select with where clause, SQL constraints, concepts of join – inner, outer
Hadoop
Understanding Big Data and Hadoop
Hadoop Architecture and HDFS
Hadoop-Map-Reduce Framework
Advanced Map-Reduce
Apache Pig
Apache Hive
Advanced Hive and HBase
Advanced HBase
Processing Distributed Data with Apache Spark
Oozie
Hadoop Project
Python
Basic Programming in Python
Numpy
Pandas for EDA
Matplotlib for Data Visualization
Scikit Learn for Machine Learning
Tableau
Getting Started with Data
Connecting to Data
Visual Analytics
Dashboards and Stories
Mapping
Calculations
How To make analytical charts
c. Advance Analytics
Machine Learning

Introduction to Neural Networks and Deep Learning
SVM and Naïve Bayes
Advanced Decision trees like Ripper,C5.0 Random Forest
forecasting numeric data
dimensionality reduction
Boosting algorithms including Adaboost and Xgboost
Hyper-parameter tuning
Volatility models such as ARCH and GARCH
Advanced Clustering and Classification
Advanced Linear Regression processes
R Packages and there Features
Text Mining
Intro to text mining and applications 
TM package in R
Applications of Regular expression
Sentiment Analysis
Ensemble Agreement
Topic Modelling
Network analysis of tweets
Clustering in Text documents
Marketing Analytics
Marketing Measurement Strategy
Price and Promotion Analytics
Competition Analysis and Market Segmentation
Product Distribution and Sales
Marketing Mix Modeling(MMM)
Marketing Metrics
Campaign Analytics and Channel Management
Forecasting
New product Analytics
Customer Lift cycle analysis
Customer Loyalty Analysis
Domain based Case Studies
( Proschool will provide basic theory videos for domain understanding and Analytical case studies will be conducted in the classroom)
Retail Analytics
Overview of the Retail Industry
Customer Analytics
Merchandizing Analytics
Store Operations
E-commerce and Marketing
Inventory analysis
Domain based Case Studies
( Proschool will provide basic theory videos for domain understanding and  Analytical case studies will be conducted in the classroom)
Financial AnalyticsDomain Based Case Studies
HR AnalyticsDomain Based Case Studies
Start-up ProjectsReal Time Project with a start-up
Placement Prep
CV preparation
Group Discussion
Interview Preparation 
Presentation techniques

Why Proschool

IMS Proschool is helping students to identify and prepare themselves for careers of the future. IMS Proschool belong to the IMS group that was ranked among the most trusted education brands in the country and has a rich history of over forty years. Since 2007, IMS Proschool has created new age programs in areas such as financial modelling, management accounting etc. IMS Proschool started Analytics programs in 2016 and has become a leading player within two years.

Our course has been designed after extensively researching  candidates’ skills preferred by  over 100 analytics related companies  in India like ZS, Musigma, Absolutdata, Fractal Analytics, Flipkart, Amazon, IBM and many more. We have included 95% of the preferred skills such as R, SAS, Python, Big data, SQL etc to make our program more desirable for recruiters.

Our research can be best portrayed through the following chart.




Value for money program:

You can refer to the following table to check how our course differs from courses of others Institutes:



Institutional Tie-Ups

NSDC: Proschool is funded by the National Skill Development Centre (GOI) and launches various skill development programs under its aegis.

NCFM: Largest certification board in India, Proschool’s Financial Modeling and Business Analytics program  are certified by the NSE Academy.

CFA Institute: We are the official prep providers of CFA Level I, world’s best course in Investment Banking.

CIMA: Proschool is an award-winning learning partner of Chartered Institute of Management Accountants which is a UK based institute for globally accredited management accountancy course.

Career Opportunities

Data Analytics is the science of analyzing data to find out patterns that will be helpful in developing strategies.  Its usage can be found in almost every industry.

Following is an indicative list of roles you can play in the analytics industry - 

●   Data engineers
They are responsible for maintaining, testing and evaluating data. They are the database engineers In other words, they lay the foundations that help data analysts and scientists to work on, so that they can easily retrieve the data they have been looking for.

●   Data analysts
Data analysts help you to visualise and interpret the data and look for hidden insights. As a business or data analyst a candidate will be required to be extremely good in communications and data manipulation. You’ll be required to decode the given data and help the manager understand it with the help of visuals. A business analyst performs a very niche role of helping the business identify and track patterns which will help them grow.

●   Data Scientists 
A data scientist is someone who is proficient with dealing with a large amount of data, cleansing it and creating models for machines. Typically, a data scientist will help businesses study user activity and help in providing valuable behavioural insights.

●   Business Analysts
Understand the business requirement & define data requirements to provide solutions to the business case along with fetching & analysing.

●   Machine Learning Developers
A machine learning developer is expected to multi-task in product management, development, and design teams to build new features that solve customer challenges at hand, and predictive models for the future, by researching trends in the big data analytics.

●   BIG Data Analysts
A Big Data analyst is someone who is more efficient in analysing the Big Data which is one of the major issues amongst the companies, presently.

FAQs

Data science is recommended for those who are looking for a career shift  or wanting to grow in their analytics career.
A Capstone project is a unique learning opportunity derived from the coursework provided by some of the  top tire universities abroad. It focuses on learning simulated  by a real-life scenario. 
Engineers possess technical expertise. Their domain knowledge, when combined with the analytics skill sets, will be a formidable force. Such individuals will be able to innovate and design new systems for their clients. Any person who is genuinely interested in analytics, can benefit from this course.
Role of commerce graduates in the field of business and finance is gradually undergoing a complete transformation.  They are no longer expected to be merely good in finance, but should also possess skill sets  to analyze data and help management make smart decisions. Even if you’re a budding entrepreneur, data science can be pivotal to help your business grow.
1)  Capstone Projects
2)  Certification from NSE Academy
3)  Affordable fees
4)  Training from Industry experts
5)  Value for Money
6)  Industry Coverage for around 8-10 sectors
7)  Real Time Start-up Projects 
8)  Domain based case studies
9)  Domain theory based video sessions