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Executive Professional Certification Program in Generative AI & Business Analytics

5,515 Ratings

Unlock your expertise with the Executive Professional Certification Program in Generative AI & Business Analytics in collaboration with IITI DRISHTI CPS, IIT Indore in just 7 months.

  • Master most in demand skills like Gen AI & prompt Engineering, Machine Learning, Python, ETL, & more.
  • Learn Generative AI & Business Analytics from IIT faculty & industry experts
  • Leverage generative AI to uncover valuable business insights and drive innovation
  • Get Executive Professional Certification in Generative AI & Business Analytics from IIT Indore DRISHTI CPS (Technology Innovation Hub of IIT Indore)
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Learning Format

Online Bootcamp

Live Classes

7 Months

IIT Indore DRISHTI CPS

Certification

Campus Immersion

IIT Indore

EMI Starts

at ₹8000/month*

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About Program

This course is curated for learners to enhance their skills in generative AI & business analytics. Work on real world projects & multiple case studies to master the skills of data analysis and business decision making.

Key Highlights

50+ Live Sessions across 7 Months
IIT Indore DRISHTI CPS Certification
Flexible Schedule
Lifetime Free Upgrade
1:1 with Industry Mentors
Multiple case studies and project works
Job Assistance with Intellipaat
Resume Preparation and LinkedIn Profile Review
24/7 Support
No-cost EMI Option

About IIT Indore DRISHTI CPS

IIT Indore is the eighth IIT established in 2009 in India. IIT Indore DRISHTI CPS Foundation is a Technology Innovation Hub (TIH) setup at IIT Indore under the aegis of National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS) with a focus on System Simulation, Modelling & Visualisation.

Achievements

  • Ranked 14th among engineering colleges in India in 2023 – NIRF
  • Won Global Best M-GOV Awards gold medal with their blockchain receipt app “Blockbill in 2023.
  • IIT Indore ranked 201 globally and 2nd in India in Computer Science in 2022
Executive Professional Certification Program in Generative AI and Business Analytics Click to Zoom

Career Transition

59% Average Salary Hike

45 LPA Highest Salary

850+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Who can apply for the Generative AI & Business Analytics Online Course?

  • Under graduates, Fresh graduates looking to build their career in Gen AI & Business Analytics
  • Working professionals & Tech enthusiasts who want to master Generative AI & Business Analytics tools and skills.
  • Entrepreneurs who want to use AI to increase productivity
who can apply

Skills to Master

Excel Analytics

Data Transformation with SQL

ETL Processes

Python

Mix Market Modeling

Price Optimization Modeling

Generative AI

Prompt Engineering

Statistical Modeling

Predictive Analytics

Risk Analytics

Customer Analytics

BI Reporting

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Tools to Master

python 2 SQL TensorFlow Adv Excel Power BI 1 Langchain Scikit Learn numpy 2 pandas matplotlib Seaborn huggingface
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Meet Your Mentors

Curriculum

Live Course

Learn Fundamentals of Excel 

  • Understanding the basics of Reading the Data
  • Learn Referencing in formulae,
  • Working with the Name Range, Logical Functions, Conditional Formatting, Advanced Validation, and Dynamic Tables in Excel, Sorting and Filtering
  • Elaborate on the working of Charts in Excel, Pivot tables, Dashboards, Data, and File Security
  • What are VBA Macros, Ranges, and Worksheets in VBA?
  • Learn how to use IF conditions, loops, and Debugging

Diving Excel with Data Analytics

  • Performing the Handling of Text Data, Splitting, combining, and data imputation on text data
  • Practical understanding of Dates in Excel and Data Conversion
  • Understanding the concept of handling missing values
  • What is Data Cleaning?
  • How to use the Tables in Excel

Concepts of Data Visualization with Excel

  • Learn how to visualize Charts, Pie charts, Scatter, and bubble charts
  • Visualizing the data using Bar charts, Column charts, Line charts, and maps
  • How to use the Matrices, Cards, and Tiles in Excel

Learning Excel Power Tools

  • Explain the uses of Power Pivot, Power Query, and Power View

Solving Classification Problems Scenario using Excel

  • Solving Binary Classification Problems, Confusion Matrix, AUC, and ROC curve
  • Understanding how to utilize Multiple Classification Problems

Grasp Information Measure in Excel

  • Grasp the concepts of Probability, Entropy, and Dependence
  • Define Mutual Information

Learn Regression Problems Using Excel

  • Elaborate the Standardization, Normalization, and Probability Distributions
  • How to use Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, and Correlation
  • Describe the concepts of Linear Regression, Logistic Regression, Error in regression, and information gain using Regression with examples
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Basics of SQL

  • Understanding the Fundamentals of Structured Query Language
  • Learn how to use SQL Tables, Joins, and variables with examples

Learn Advanced SQL

  • How to use SQL Functions, Subqueries, Rules, and Views
  • Elaborate the concept with examples of Nested Queries, string functions, and pattern matching
  • Solving the problem scenario of Mathematical functions and date-time functions

Concepts of User-Defined Functions

  • Explain Types of UDFs, Inline table value, and multi-statement tables
  • What are stored procedures?
  • Describe the rank function, SQL ROLLUP

Optimization and Performance in SQL

  • Learn how to optimize using record grouping, searching, and sorting
  • Define clustered indexes and common table expressions.
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Overview of ETL Testing

  • Learn the concepts of ETL testing
  • Describe the Life cycle of ETL testing and database concepts
  • Using ETL in Business Intelligence
  • Learn how OLTP and OLAP differ from one another
  • What is data warehousing?

Examine Testing for databases and data warehousing

  • Elaborate the RDBMS
  • Notions of relational databases
  • Testing differences between database and data warehousing
  • How to use the integrity constraints.

Working with the ETL Testing Scenarios

  • What is the data warehouse workflow/
  • Analyze the ETL Testing scenarios
  • How to perform the ETL Mapping
  • Data Warehouse Testing vs. ETL testing
  • Define Data Mismatch & Data Loss Testing with examples

Dive into Correctness, Completeness, Quality, and Data Validation

  • Overview of the different testing situations
  • Describe the structure validation
  • How to use constraint validation
  • How to manage the data’s correctness, completeness, and quality
  • What is data validation and what are its types?
  • Describe the pros and cons of negative testing

Perform Data Checks with SQL

  • Utilizing SQL to verify data
  • Describe the database structure
  • How to run the SQL Scripts with examples

Explore Reports & Cube testing

  • How to use the Reports and Cube Testing
  • How Business Intelligence Testing Should Be Conducted
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Getting Started With Python Environment Setup and its Essentials

  • Explain the Python language and how it works.
  • Describe the Features and advantages of Python over other programming languages
  • How do install Python (Windows, Mac, and Linux Distributions for Anaconda Python)?
  • Elaborate on the process of Deploying Python IDE
  • Explain the fundamentals of Python commands, data types, variables, and keywords

Break Down the Python Language Basic Constructs

  • Explain the Built-in data types in Python
  • Learn how to use the classes, modules, Str (String), Ellipsis Object, Null Object, Ellipsis, and Debug
  • What are the basics of operators, comparison, arithmetic, slicing and slice operators, logical, and bitwise?
  • Learn how to use the Loop and control statements while, for, if, break, else, and continue

Articulate Object-Oriented Programming Concepts in Python

  • How do you create a Python program that uses the OOP concepts?
  • Learn how to connect to a database
  • Learn the concepts of Classes and Objects in Python
  • Describe the OOPs paradigm and learn important concepts in OOPs like polymorphism, inheritance, and encapsulation
  • Explain the working of Python functions, return types, and parameters
  • How do we use the Lambda expressions?

 Establishing Database Connection

  • Describe the concepts of databases, and what is the need for databases?
  • How do configure and install MySQL on Windows?
  • Learn how to create Database connections using Python

Function of NumPy for Mathematical Computing

  • Elaborate the arrays and matrices and their differences
  • Describe the features of Broadcasting array math and indexing of the array
  • Describe the features and relations between Standard deviation, conditional probability, correlation, and covariance

Working with SciPy for Scientific Computing Tools

  • Elaborate the SciPy and its functions
  • What functions are built on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages, and SciPy with Bayes’ Theorem?

Guide of Matplotlib for Data Visualization

  • What is the Python formula for plotting graphs and charts?
  • Working with line, scatter, bar, histogram, 3D, Matplotlib’s API, and subplots in various ways

Working With Exception Handling

  • Describe the functions of Exception Handling
  • Exception handling scenarios and their implementation
  • Describe the functions of Arithmetic exception
  • How to effectively raise an Exception?
  • Random List Definition and Using It in a Jupyter Notebook
  • Explain the Value Error in Exception Handling with an example
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Fundamentals of Machine Learning

  • Elaborate supervised and unsupervised learning with examples
  • Explain how to use scikit-learn and Keras

Working with Regression

  • Learn the Regression problems in machine learning
  • Learn how to identify a regression problem using dependent and independent variables.
  • Describe how to train the model for a regression problem with examples
  • Explore how to assess the model for a regression problem.
  • How to maximize the regression model’s effectiveness

Working with Classification

  • Learn the classification problems in machine learning
  • Learn how to identify a classification problem using dependent and independent variables
  • Describe how to train the model in a classification problem with examples
  • Explore how to assess the model for a classification problem
  • How to maximize the classification model’s effectiveness

Working with Clustering

  • Learn the clustering problems in machine learning
  • Learn how to identify a clustering problem using dependent and independent variables.
  • Describe how to train the model in a clustering problem with examples
  • Explore how to assess the model for a clustering problem
  • How to maximize the clustering model’s efficiency

Build and Train with Supervised Learning

  • Describe Linear regression using instances and real-world applications
  • Explain the Logistic Regression in detail with Examples and Uses
  • Articulate the Decision Tree using instances and real-world applications
  • Explain Random Forest in detail with Examples and Uses
  • Describe Support Vector Machine using instances and real-world applications
  • Define Gradient Descent in detail with Examples and Uses
  • What are K-Nearest Neighbors, with examples and practical uses?
  • Give an example and use of Time Series Forecasting.

Build and Train with Unsupervised Learning

  • What K-means is, how it works, and an example
  • Describe the Dimensionality reduction technique
  • How to perform the Linear Discriminant Analysis
  • Explanation of Principal Component Analysis
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Learn the Basics of Power BI

  • Elaborate the working and importance of Power BI
  • Use cases and Business Intelligence Tools
  • Understanding the concept of Data Warehousing
  • What are the Power BI components?
  • How to use the Power BI Desktop
  • Learn the essentials of workflows and reports
  • Discover how to use Power BI for Data Extraction.
  • What are SaaS Connectors?
  • Using an Azure SQL database with large datasets
  • Learning how to work with R and Python with Power BI
  • Guide for a Power Query Editor
  • Using an Advance Editor
  • Learn how to use Query Dependency Editor
  • What are Data Transformations?
  • Methods for Combining and Shaping Data
  • Explain the use of M Query and Hierarchies in Power BI

Overview of DAX

  • Learn about Data Modeling and DAX,
  • How to use the Time Intelligence Functions
  • Using the DAX Advanced Features

Data Visualization Analytics in Power BI

  • Describe the working of Slicers, filters, and Drill Down Reports
  • Creating visuals using Power BI Query, Q&A, and Data Insights
  • How to set up and establish Power BI Settings, Administration, and Direct Connectivity
  • Differences between the Embedded Power BI API and Power BI Mobile
  • Working with Power BI Advance and Power BI Premium
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Fundamentals of Programming in Generative AI

  • Learning essentials of Variables, Operators, and Data Types
  • How to use Loops and Conditional Statements
  • Describe the Functions and Exception Handling
  • What is Object Oriented Programming?
  • How to perform Data Cleaning and Preprocessing with Numpy and Pandas
  • Elaborate the Machine Learning Use Cases
  • Grasp the fundamentals of Natural Language Processing
  • How to use Text Processing and Classification with examples

Transformers

  • Introduction to Transformers
  • Transformer Architecture
  • Working of Transformers
  • Applications of Transformers

BERT

  • Introduction to BERT
  • BERT Architecture
  • Working of BERT
  • Applications of BERT

GPT

  • Introduction to GPTs
  • GPT Architecture
  • Working of GPTs
  • Applications of GPT

LLM

  • Introduction to LLMs
  • LLM Architecture
  • Working of LLMs
  • Applications of LLM

Recommendation: Chatbot Powered by Generative AI

  • Methods for Developing Workflow and Product Design
  • Learn about Text Generation with Transformers, RLHF, and pre-trained LLMs.
  • Working with the fundamentals of LangChain
  • Explain how to Use Recommendation Engines
  • Performing Evaluation Metrics for various models
  • Using Prompt Engineering
  • Using Gradio to Develop Generative AI Applications
  • Creating and Distributing Recommended using Gradio
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Program Highlights

400+ Hrs Instructor-Led Training
50+ Live Sessions across 7 Months
IIT Indore DRISHTI CPS Certification
24/7 Support

Projects

Projects are a key component of the Executive Professional Certification Program in Generative AI & Business Analytics, providing you with practical experience to reinforce your knowledge and skills in these cutting-edge areas.

Reviews

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Career Services By Intellipaat

Career Services
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Placement Assistance
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Exclusive access to Intellipaat Job portal
Mock Interview Preparation
1 on 1 Career Mentoring Sessions
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Career Oriented Sessions
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Resume & LinkedIn Profile Building
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Admission Details

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

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Submit Application

Tell us a bit about yourself and why you want to join this program

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Application Review

An admission panel will shortlist candidates based on their application

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Admission

Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

₹ 1,29,048 (Inclusive of All)

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EMI Starts at

₹ 8,000

We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs

Financing Partners

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The credit facility is provided by a third-party credit facility provider and any arrangement with such third party is outside Intellipaat’s purview.

Upcoming Application Deadline 8th Dec 2024

Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.

Program Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 8th Dec 2024 08:00 PM - 11:00 PM IST Weekend (Sat-Sun)
Regular Classes 8th Dec 2024 08:00 PM - 11:00 PM IST Weekend (Sat-Sun)
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Frequently Asked Questions

What can you expect from this Generative AI and Business Analytics Course?

This Generative AI and Business Analytics Course provides a comprehensive understanding of AI techniques and their application in business analytics. It covers topics like machine learning, data analysis, data visualization, and generative AI models. You’ll gain hands-on experience with tools and techniques, preparing you for roles in data-driven decision-making.

You should take this Courses online because:

  • There are over 64,000 AI and Business Analytics jobs listed in the USA. – LinkedIn
  • 18,000+ job openings are available for AI and Business Analysts in India. – LinkedIn
  • US$1,20,000 and ₹8,00,000 is the average annual pay of Business Analysts in the USA and India. – Indeed

This Generative AI & Business Analytics course helps you master the skills required by top employers in the domain of AI & Business Analytics. Latest. You will learn from IIT faculty and top Industry experts . A lot of hands-on projects, assignments and real-world case studies are provided to ensure practical, job-ready skills delivered through this program. Additionally, it includes dedicated career support to maximize job placement opportunities.

You can apply for the following Generative AI & Business Analytics related job profiles:

Job Role Average Salary (India) Average Salary (US)
Generative AI Business Analyst ₹900,000 – ₹1,600,000 $110,000 – $170,000
Data Scientist ₹1,200,000 – ₹2,000,000 $140,000 – $200,000
Business Intelligence Analyst ₹800,000 – ₹1,400,000 $90,000 – $150,000
Marketing Analyst ₹700,000 – ₹1,200,000 $80,000 – $100,000

The course demonstrates how Generative AI can enhance business analytics by providing advanced data generation techniques, improving predictive models, and enabling more sophisticated data analysis.

Yes, the course includes practical examples and case studies to help you understand how generative AI and business analytics are applied in real-world scenarios.

It is not mandatory to have coding or programming skills, but if you have, it will count as a plus point. To make a career in Artificial Intelligence or Business Analytics, you should have strong communication skills, domain knowledge, and an in-depth understanding of Business Analysis tools. A strong forte in aspects of problem-solving is a plus.

Organizations such as Google, Amazon, IBM, Microsoft & many top startups actively recruit professionals specializing in Generative AI and Business Analytics. Additionally, consulting firms like McKinsey, Deloitte, and Accenture, as well as financial institutions like JPMorgan Chase and Goldman Sachs, seek experts in these fields to enhance their data-driven decision-making and innovation capabilities.

Recorded sessions are typically made available for review if you miss a live session. You can watch these recordings at your convenience and catch up on the missed content.

Intellipaat offers query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail yourself of email support for all your queries. We can also arrange one-on-one sessions with our support team if your query is not resolved through email. However, 1:1 session support is given for 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have completed the training and moved to the placement pool after clearing the PRT (Placement Readiness Test). More than 500+ top MNCs and startups hire Intellipaat learners. Our alumni work with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work