post graduate certification in business analysis & product
TRANSCRIPT
PG Certification Program in Business Analysis & Product Management 1 | Page
Post Graduate Certification in
Business Analysis & Product Management
By E&ICT MNIT, Jaipur in collaboration with IIBA & IBM
PG Certification Program in Business Analysis & Product Management 2 | Page
Table of Contents
1. About the Program 2. About E&ICT MNIT, Jaipur 3. Collaborating with IIBA & IBM 4. About Intellipaat 5. Key Features 6. Placement & Career Services 7. Eligibility Criteria & Application Process 8. Learning Path 9. Course Advisors 10. Program Curriculum 11. Certification 12. Success Stories 13. Contact Us
PG Certification Program in Business Analysis & Product Management 3 | Page
About the Program
This PG certification in Business Analysis & Product Management by E&ICT Academy,
MNIT (Malviya National Institute of Technology), Jaipur will provide extensive training on
agile methodologies, Tableau, SQL for business analytics, etc. and with a focus on
industry-based projects for hands-on experience. This course includes the modules of IIBA
CBAP & CBDA certification as well as you will master data analysis with IBM modules and
receive IBM certificate for the same. The course has been carefully brought together by
the Industry experts & top faculty at MNIT.
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About E&ICT Academy MNIT, Jaipur
Electronics & ICT Academy MNIT, Jaipur (E&ICT MNIT, Jaipur) is an initiative supported by MeitY, Govt of India. The courses provided by us lay an emphasis on bridging the gap between industry demand and academic approach to learning and provide a foundation to build your career in top IT companies.
In this program, you will:
Get Live Lectures from the MNIT faculty
Receive PG certificate from E&ICT, MNIT & Intellipaat
Alumni status of E&ICT, MNIT Jaipur
Key Achievement of MNIT, Jaipur:
Ranked 35 in NIRF 2020 Ranking among top engineering colleges
Ranked 23 by the Week in 2020 for engineering
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Program in Collaboration with IIBA and IBM
The IIBA supports and promotes the discipline of business analysis and strives to help
Business Analysts sharpen their skills. They offer education and content to help learners and
professionals open up their career paths. IBM is a giant player in the market and its carefully
designed module will help anyone jump up the career ladder.
Benefits for students from IIBA
Industry-recognized certification from IBM
Real-time projects and exercises
Earn 35 hrs PDs / CDUs for CBAP
Earn 24 hrs PDs / CDUs for CBDA
About Intellipaat
Intellipaat is one of the leading online training providers with more than 600,000 learners
across 53+ countries. We are on a mission to democratize education as we believe that
everyone has the right to quality education.
Our courses are delivered by subject matter experts from top MNCs and our world-class
pedagogy enables to quickly learn difficult topics in no time. Our 24/7 technical support
and career services will help learners jump-start their careers in their dream companies.
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Key Features
7 MONTHS OF LIVE CLASSES 24/7 SUPPORT
20+ REAL-TIME INDUSTRY PROJECTS
30+ CASE STUDIES
PG CERTIFICATION PROGRAM FROM E&ICT MNIT, JAIPUR
PROGRAM IN COLLABORATION WITH IIBA & IBM
INDUSTRY-RECOGNIZED CERTIFICATION FROM IBM
LEARN FROM MNIT
PROFESSORS AND
INDUSTRY EXPERTS
PG Certification Program in Business Analysis & Product Management 7 | Page
Career Services
Dedicated Learning Manager
Get mentored by experts, receive personalized feedback on your performance, and clarify your doubts in no time
Personalized Industry Mentor
We match your profile with the right industry mentor based on your past skills. Your mentor’s guidance will help you get prepared yourself for your dream job
Mock Interviews
Mock interviews to make you prepare for cracking interviews by top employers
3 Guaranteed Interviews
Upon completion of the assignments and projects, learners will be able to attend interviews arranged by Intellipaat with the hiring partners that includes top startups and MNCs.
Resume Preparation & LinkedIn Profile Building
Get assistance in creating a world-class resume from our career services team
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Eligibility Criteria & the Application Process
Those wishing to enroll in the Post Graduate Certification in Business Analysis &
Product Management will be required to follow the admission process mentioned
below.
Eligibility Criteria
For the admission to the Post Graduate Certification in Business Analysis & Product Management, candidates should:
Have a bachelor’s degree with an average of 50% or higher marks
Be working professionals with zeal to build a career in Business Analysis & Product Management
Application Process
The application process consists of three simple steps. Candidates have to submit
their application. An offer of admission will be made to the selected candidates, and
their application will be accepted upon the payment of the admission fee.
SUBMIT APPLICATION
Tell us a bit about yourself and why you want to join this program
APPLICATION REVIEW
Have a personal interview with our interview panel
ADMISSION LETTER
Shortlisted candidates would be offered the admission letter
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Learning Path
ELECTIVE COURSE
Data Analysis with Python by IBM
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Course Advisors & Faculty
Suresh Paritala
Solutions Architect at Microsoft, USA
A Senior Software Architect at NextGen Healthcare who has previously
worked with IBM Corporation, Suresh Paritala has worked on Big Data, Data
Science, Advanced Analytics, Internet of Things and Azure, along with AI
domains like Machine Learning and Deep Learning. He has successfully
implemented high-impact.
David Callaghan
Big Data Solutions Architect, USA
An experienced Blockchain Professional who has been bringing integrated
Blockchain, particularly Hyperledger and Ethereum, and Big Data solutions
to the cloud, David Callaghan has previously worked on Hadoop, AWS
Cloud, Big Data and Pentaho projects that have had major impact on
revenues of marquee brands around the world.
Muthusamy Manigandan Head Engineering, Amazon
Mani has 16+ years of experience in working on cloud projects for fortune
500+ companies. He comes with strong architectural and implementation
experience on AWS, Azure, GCP, along with DevOps tools.
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Program Curriculum Core Curriculum: Module 1 - Certified Business Analysis Professional (CBAP®)
1.1 Introduction to Business Analysis
Business Analysis overview
Who is a Business Analyst?
Introduction to governance body (IIBA)
Business Analysis body of knowledge
Knowledge areas of BABOK
SDLC & requirement analysis
1.2 Business Analysis Concepts and Knowledge Areas
Business Analysis core concepts and knowledge areas
Planning and monitoring
Business Analysis approach and governance
Business Analysis information management
Elicitation and collaboration
1.3 Requirement Lifecycle Management and Strategy Analysis
Trace, maintain, & prioritize requirements
Assess requirement changes and approval
Analyze current state
Define future state
Assess risks
Define change strategy
1.4 Requirement Analysis, Design Definition, Model Requirements, and Solution Evaluation
Specify model requirements
Verify and validate requirements
Define requirement architecture and design options
Measure and analyze solution performance
Assess solution and enterprise limitations
Recommend actions to increase solution values
Data model, UI model, user stories
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1.5 Agile Business Perspectives and Creating UML
Introduction to business Agile perspective
Business Intelligence perspective
Information Technology perspective
Business architecture perspective
Business Process Management perspective
1.6 Understand BA Role on the Agile Team
Write effective user stories and acceptance criteria
Develop backlogs into great products
BA role in new age Business Analysis
1.7 Underlying Competencies of a Business Analyst & Microsoft Visio
Business Analyst underlying competencies
BA Skills
Soft skills, leadership and personal development
UML diagrams using Microsoft Visio
Types of flowcharts, cross-functional flowcharts
Module 2 - Certification in Business Data Analytics (CBDA®)
2.1 Data Science and Analytics Fundamentals
Introduction to data science and analytics
Use cases in data science and analytics
Data science life cycle
Data Analytics: Types
AI and Machine Learning: Overview
2.2 CBDA: Introduction
CBDA: Overview
What is Business Data Analytics?
Eligibility criteria
Six Business Data Analytics domains
2.3 Business Analysis and Data Analytics
Business analysis in data analytics projects
Comparison between business analysis and data analytics
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2.4 Business Data Analytics Domains: Introduction
Domain 1: Identifying the Research Questions
Defining business problems or opportunities
Identifying and understanding stakeholders
Current state assessment
Defining the future state
Formulation of research questions
Planning the Business Data Analytics approach
Selection of techniques for the identification of research questions
Domain 2: Source Data
Data collection planning
Determination of datasets
Data collection
Data validation
Domain 3: Data Analysis
Developing a Data Analysis plan
Data preparation
Data exploration
Performing data analysis
Assessment of the analytics and system approach
Domain 4: Interpreting and Reporting Results
Validating the understanding of stakeholders
Planning for stakeholder communication
Determining the communication requirements of the stakeholders
Deriving insights from data
Documentation and communication of findings from the completed analysis
Selection of techniques for interpreting and reporting results
Domain 5: Using Results to Influence Business Decision-making
Action recommendation
Implementation plan development
Change management
Guiding the organizational-level strategy for Business Data Analytics
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Organizational strategy
Talent strategy
Data strategy
2.5 Techniques
Business simulation
Business visualization
Concept modeling
Data dictionary, flow diagrams, mapping, and storytelling
Decision modeling and analysis
Descriptive and inferential statistics
Extract, Transform, and Load (ETL)
Exploratory data analysis
Hypothesis formulation and testing
Interface analysis
Optimization
Problem shaping and reframing
Stakeholder list, map, and personas
Survey and questionnaire
Technical visualizations
The big idea
3-minute story
Module 3 - Agile Methodologies for Project Management
3.1 Introduction to Agile Scrum
Agile Scrum overview
Agile project principles
Sprint and Increment in Agile Scrum
Scrum theory
Other Agile Frameworks
3.2 Scrum Team and Artifacts and Events
Scrum team and Scrum Master
Scrum roles
Scrum flow
Scrum artifacts: product backlog
Artifacts transparency
Scrum events: sprint planning and retrospective
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Agile estimating, planning, monitoring, and control
3.3 Project Management Using Jira
Introduction to Project Management in Jira
Jira issue types
Scrum & Kanban boards
Customizing board settings
Release and backlog management
Jira reports
Module 4 - UML 2.0 4.1 Class diagram
4.2 Component diagram
4.3 Composite structure diagram
4.4 Deployment diagram
4.5 Object diagram
4.6 Package diagram
4.7 Profile diagram
4.8 Activity diagram
4.9 State machine diagram
4.10 Use case diagram
4.11 Communication diagram
4.12 Interaction overview diagram
4.13 Sequence diagram
4.14 Timing diagram
Module 5 - Career Essentials 5.1 Communication skills
5.2 Leadership skills
5.3 Problem-solving skills
5.4 Business knowledge
5.5 IT knowledge
Module 6 - Data Visualization using Tableau
6.1 Introduction to Data Visualization and Power of Tableau
What is data visualization?
Comparison and benefits against reading raw numbers
Real use cases from various business domains
Examples using Tableau
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Installing Tableau, Tableau interface, connecting to DataSource, Tableau data types
Data preparation
6.2 Architecture of Tableau
Installation of Tableau Desktop
Architecture of Tableau
Tableau interface
How to start with Tableau
The ways to share and export the work done in Tableau
Hands-on Exercise:
Play with Tableau desktop, learn about the interface, share and export existing works
6.3 Working with Metadata and Data Blending
Connection to Excel
Cubes and PDFs
Management of metadata and extracts
Data preparation
Joins and Union
Hands-on Exercise:
Connect to Excel sheet to import data, use metadata and extracts, manage NULL values, clean up data
before using, perform the join techniques, execute data blending from multiple sources
6.4 Creation of Sets
Mark, highlight, sort, group, and use sets
Constant sets
Computed sets, bins, etc.
Hands-on Exercise:
Use marks to create and edit sets, highlight the desired items, make groups, apply to sort on results, make
hierarchies among the created sets
6.5 Working with Filters
Filters
Filtering continuous dates, dimensions, and measures
Interactive filters, marks card, and hierarchies
How to create folders in Tableau
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Sorting in Tableau, types of sorting, filtering in Tableau, Types of filters
Filtering the order of operations
Hands-on Exercise:
Use the data set by date/dimensions/measures to add a filter, Use an interactive filter to view the data,
Customize/remove filters to view the result
6.6 Organizing Data and Visual Analytics
Using formatting pane
Formatting data using labels and tooltips
Edit axes and annotations
K-means cluster analysis
Trend and reference lines
Visual analytics in Tableau
Hands-on Exercise:
Apply labels and tooltips to graphs, annotations, edit axes’ attributes, set the reference line, perform k-
means cluster analysis on the given dataset
6.7 Working with Mapping
Working on coordinate points
Plotting longitude and latitude
Editing unrecognized locations
Customizing geocoding, polygon maps, WMS: web mapping services
Working on the background image, including add image
Plotting points on images and generating coordinates from them
Map visualization, custom territories, map box, WMS map
Create map projects in Tableau
Creating dual axes maps, and editing locations
Hands-on Exercise:
Plot longitude and latitude on a geo map, edit locations on the geo map, custom geocoding, use images of
the map and plot points, find coordinates, create a polygon map, use WMS
6.8 Working with Calculations and Expressions
Calculation syntax and functions in Tableau
Various types of calculations
LOD expressions, including concept and syntax
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Aggregation and replication with LOD expressions
Nested LOD expressions
Levels of details
Quick table calculations
The creation of calculated fields
Predefined calculations
How to validate
6.9 Working with Parameters
Creating parameters
Parameters in calculations
Using parameters with filters
Column selection parameters
Chart selection parameters
Parameters in the filter session
Parameters in calculated fields
Parameters in the reference line
Hands-on Exercise:
Creating new parameters to apply on a filter, passing parameters to filters to select columns, passing
parameters to filters to select charts
6.10 Charts and Graphs
Dual axes graph
Histograms, single and dual axes, box plot
Charts
Maps
Market basket analysis (MBA)
Using show me, text table, and highlighted table
Hands-on Exercise:
Plot a histogram, tree map, heat map, funnel chart, and more using the given dataset, perform market
basket analysis (MBA) on the same dataset
6.11 Dashboards and Stories
What is a dashboard?
Building and formatting a dashboard
Best practices for making dashboards
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Creating stories
Adding annotations
Tableau joins, Types of joins, Tableau field types
Saving as well as a publishing data source
Hands-on Exercise:
Create a Tableau dashboard view, include legends, objects, and filters, make the dashboard interactive, use
visual effects, annotations, and descriptions to create and edit a story
6.12 Tableau Prep
Introduction to Tableau Prep
Getting deeper insights into the data with visualizations
Making data preparation simpler and accessible
Integrating Tableau Prep with Tableau analytical workflow
Data preparation to analysis with Tableau Prep
Module 7 - Mastering MS Excel for Business Analysis 7.1 Introduction to MS Excel & Data Extraction
7.2 Referencing in formulas
7.3 Name range
7.4 Logical functions
7.5 Conditional formatting
7.6 Advanced-level validation
7.7 Important formulas in Excel
7.8 Dynamic table
7.9 Data sorting, filtering
7.10 Chart creation techniques
7.11 Pivot tables in Excel
7.12 Data and file security
7.13 VBA Macros
7.14 Best practices of dashboards visualization
7.15 Creating dashboards
7.16 Creation of interactive components
Module 8 - SQL for Business Analytics
8.1 Introduction to SQL
Various types of databases
Structured Query Language
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Distinction between client-server and file server databases
Understanding SQL Server Management Studio
SQL Table basics
Data types and functions
Transaction-SQL
Authentication for Windows
Data control language
Identification of keywords in T-SQL
8.2 Database Normalization and Entity Relationship Model
Data anomalies
What is normalization?
Types of normalization forms
Entity-relationship model
8.3 SQL Operators
Introduction to relational databases
Fundamental concepts of relational rows, tables, and columns
Several operators (such as logical and relational), constraints, domains, indexes, stored
procedures, primary and foreign keys
Understanding group functions, the unique key
8.4 Working with SQL: Join, Tables, and Variables
Advanced concepts of SQL tables
SQL functions
Operators & queries
Table creation
Data retrieval from tables
Combining rows from tables
Deploying operators
Temporary table creation
Set operator rules
Table variables
8.5 Deep Dive into SQL Functions
SQL functions
Scalar and aggregate functions
Inline SQL functions
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General and duplicate functions
8.6 Working with Subqueries
SQL subqueries and rules
Statements and operators with which subqueries can be used
Modify subqueries
Types of subqueries
Methods to create and view subqueries
8.7 SQL Views, Functions, and Stored Procedures
Learning SQL views
Methods of working with views
Stored procedures and their key benefits
Module 9 - Machine Learning for Business You will be working on multiple projects on different domains like retail, finance, banking and learn
how Machine Learning is used to solve todays world problems.
Module 10 - Data Analysis with Python
10.1 Python Environment Setup and Essentials
Introduction to Python
Features
Python installation – Windows, Mac & Linux distribution for Anaconda Python
Deploying Python IDE
Basic Python commands, data types, variables, keywords, etc.
Hands-on Exercise
Installing Python Anaconda for Windows, Linux, and Mac
10.2 Python language Basic Constructs
Built-in data types in Python
Learn classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug
Basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise
Loop and control statements
Hands-on Exercise
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Write your first Python program, Write a Python function (with and without parameters), use Lambda
expression, write a class, create a member function and a variable, create an object, write a for loop
10.3 OOP concepts in Python
Write OOP concepts program in Python
Connecting to a database
Classes and objects in Python
OOPs paradigm
Python functions, return types, and parameters
Lambda expressions
Hands-on Exercise
Creating an application that helps to check balance, deposit money and withdraw the money using the
concepts of OOPS.
10.4 Database Connection
Database and need of database
Installing MySQL on Windows
Database connection using Python
Hands-on Exercise
Demo on Database Connection using python and pulling the data.
10.5 NumPy for Mathematical Computing
Arrays and matrices
Broadcasting of array math
Indexing of the array
Standard deviation, conditional probability, correlation, and covariance
Hands-on Exercise
How to import the NumPy module, creating an array using an ND-array, calculating standard deviation on
an array of numbers, calculating correlation between two variables.
10.6 SciPy for Scientific Computing
Introduction to SciPy
Functions building on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages,
SciPy with Bayes Theorem
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Hands-on Exercise
Importing of SciPy, applying the Bayes theorem on the given dataset
10.7 Matplotlib for Data Visualization
How to plot graph and chart with Python
Various aspects of line, scatter, bar, histogram, 3D, the API of MatPlotLib, subplots
Hands-on Exercise
Deploying MatPlotLib for creating Pie, Scatter, Line, Histogram
10.8 Pandas for Data Analysis and Machine Learning
Introduction to Python data frames
Importing data from JSON, CSV, Excel, SQL database, NumPy array to data frame
Various data operations
Hands-on Exercise
Working on importing data from JSON files, selecting record by a group, applying filter on top, viewing
records
Module 11 - Capstone Project
Substantiate your learning experience and Business Analysis skills via this practical, industry-based capstone
project based on our course and showcase your skills in the field of Product Management and Business
Analysis.
CASE STUDIES AND PROJECT WORK
Learners will work on multiple case studies and projects from different domains
as mentioned below:
1. Write Complex Subqueries
Work with SQL subqueries for use in numerous situations. Use queries like IN or NOT
IN, EXISTS or NOT EXISTS, ANY or ALL, etc.
2. Query a Large Relational Database
Work with data types, table basics, SQL functions, and SQL operators to acquire
details of customers by database querying.
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3. Calculation of Employee Bonuses
Use the if function to calculate the bonuses of all the employees at 10% of their salary.
Rate the sales employees as per the respective sales and rating scale.
4. Design a Relational Database
Convert relational design consisting of the details of various users, user accounts, user
roles, etc., in the SQL Server table.
5. Deal with Financial Data
Analyze global sales and profit by developing an interactive map, and use map styles
and layers for enhanced visualization.
6. Work with Agricultural Data
Display district-wise data to build an interactive treemap with state labels. The districts
must be displayed by hovering on the respective states.
7. Planning Poker
Each estimator gets a deck of cards and each card has a valid estimate written on it.
Each estimator selects a card as an estimate and the cards are turned over to discuss
differences and re-estimate until estimates converge.
8. Identify the Global Mortality Rate Due to COVID-19
Analyze and create a dashboard to gain insights into the COVID-19 cases. Use a world
map to compare the confirmed cases and death cases worldwide.
9. Work with the Customer Data of the UK Bank
Analyze and create a dashboard to gain insight from the UK bank’s customer data.
Build an asymmetric drop-down consisting of the region and the corresponding user
details
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Certification
After the completion of the course, candidates will get certificate from E&ICT
MNIT, Jaipur
Also IBM course completion certificate will be provided
Intellipaat Success Stories
PG Certification Program in Business Analysis & Product Management 26 | Page
Vishal Pentakota
The best part of this online course is the series of hands-on demonstrations
the trainer performed. Not only did he explain each concept theoretically
but implemented all those concepts practically. Great job! A must go for
beginners.
Shreyashkumar Limbhetwala
I want to talk about the rich LMS that Intellipaat’s training offered. The
extensive set of PPTs, PDFs, and other related course material were of the
highest quality, and due to this my learning with Intellipaat was excellent.
Giri Karnal
I had taken the training course. Since there are so many technologies
involved in this course, getting your query resolved at the right time becomes
the most important aspect. But with Intellipaat, there was no such problem as
all my queries were resolved in less than 24 hours.
Sharath Reddy Yellapati
The course material was very well organized. The trainer explained the
basics of each module to me. All my queries were addressed clearly. The
trainer also made me realize how important this course is for beginners in
the IT stream.
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CONTACT US
INTELLIPAAT SOFTWARE SOLUTIONS PVT. LTD.
Bangalore
AMR Tech Park 3, Ground Floor, Tower B, Hongasandra Village, Bommanahalli, Hosur Road, Bangalore – 560068
USA
1219 E. Hillsdale Blvd. Suite 205,
Foster City, CA 94404
If you have any further queries or want to have a conversation with us, then do call us.
IND: +91-7022374614 | US: 1-800-216-8930 E-mail – [email protected]