Data Analytics & Generative AI Program
August 15, 2024 2025-08-14 19:43Data Analytics & Generative AI Program
Data Analytics with Generative AI Course | Modern Analytics Training
Combines data analytics with advanced Generative AI tools.
Provides practical experience through real-world projects.
Taught by industry professionals with deep expertise.
Covers essential tools like Python, SQL, Tableau, and cutting-edge AI technologies.
Opens doors to diverse roles in data science, AI, and business analysis.
Keeps you current with the latest technologies and industry trends.
Offers skills that are applicable across various industries and job roles.
Provides opportunities to network with peers and professionals in the data and AI fields.
Combine Traditional Analytics with AI-Powered Insights
Weekly sessions with industry professionals
Dedicated Learning Management Team
375 hours of hands-on learning experience
Over 120 hours live sessions spread across 05 months
150 hours of self-paced Learning
Learn from IIT Faculty & Industry experts
More than 40+ industry-related projects and case studies
Personalised mentorship sessions with industry experts
24/7 Support
Dedicated Learning Management Team
1:1 Mock Interview
No-Cost EMI Option
Designed for both working professionals and fresh graduates
High Demand and Career Opportunities
Competitive Edge and Innovation
Problem-Solving and Critical Thinking
Weekly sessions with industry professionals
Dedicated Learning Management Team
375 hours of hands-on learning experience
Over 120 hours live sessions spread across 05 months
150 hours of self-paced Learning
Learn from IIT Faculty & Industry experts
More than 40+ industry-related projects and case studies
Personalised mentorship sessions with industry experts
24/7 Support
Dedicated Learning Management Team
1:1 Mock Interview
No-Cost EMI Option
Designed for both working professionals and fresh graduates
High Demand and Career Opportunities
Competitive Edge and Innovation
Problem-Solving and Critical Thinking
Why Join Data Analytics & Generative AI Program ?
Upcoming Batch:-
7th September 2025
14th September 2025
Data Analytics & Generative AI Program Overview
This program helps participants to be proficient in both data analysis and AI. The program includes Advanced Excel, Python, Basic Statistics, SQL & data visualization with Tableau/Power BI. It also delves into Generative AI technologies such as Hugging Face Transformers, LLMs and DALL-E 2, MidJourney, GANs, RAG, LangChain to give you a strong foundation in data management and cutting-edge advanced AI tools.
ENROLL NOW & BOOK YOUR SEAT AT FLAT 50% WAIVER ON FEE
Batch Schedule
| Batch | Batch Type |
|---|---|
| Online Live Instructor Led Session | Full-Time |
| Online Live Instructor Led Session | Part-Time |
Regional Timings
| Region | Time |
|---|---|
| IST (India Standard Time) | 09:00 PM – 12:00 AM |
| Bahrain, Qatar, Kuwait, Saudi Arabia | 06:30 PM – 09:30 PM |
| UAE / Oman | 07:30 PM – 09:00 PM |
Talk to our Corporate training advisor
Data Analytics & Generative AI Program Objectives
The Program is aimed at offering essential knowledge in the key field areas related to data analysis, Python programming and statistical techniques useful for decision making based on data. This meant they wanted me to work more on SQL for database management and Tableau for data visualization. Further, the course also exposes learners to state-of-the-art Generative AI technologies such as: Hugging Face Transformers, LLMs, DALL-E 2, GANs so they could use more advanced tools in their projects. The programme aims to make the participants well versed with data analytics and AI.
Why Learn Data Analytics & Generative AI Program?
Program Advantages
Master essential tools like Advanced Excel, Python, SQL, Tableau, and advanced Generative AI technologies.
Learn up-to-date practices that match current market demands.
Apply knowledge through real-world projects and hands-on exercises.
Develop advanced skills in Generative AI, including LLMs, DALL-E 2, and GANs.
Equip yourself with versatile skills applicable across various sectors.
Stay ahead with cutting-edge tools that shape the future of data and AI.
Master essential tools like Advanced Excel, Python, SQL, Tableau, and advanced Generative AI technologies.
Learn up-to-date practices that match current market demands.
Apply knowledge through real-world projects and hands-on exercises.
Develop advanced skills in Generative AI, including LLMs, DALL-E 2, and GANs.
Equip yourself with versatile skills applicable across various sectors.
Stay ahead with cutting-edge tools that shape the future of data and AI.
Data Analytics & Generative AI Program Certification
Data Analytics & Generative AI Program Learning Path/Curriculum
Module 01 - Python
Lecture 01: Introduction to Python, Why Python, Variables, Data Types, Type Casting, Strings, Indexing
Lecture 02: Operators and Conditional Statements, Looping Statements and its Control Statement
Lecture 03: Lambda Functions, *args, **kwargs, Functions
Lecture 04: Data Structures - List, Tuple, and List Comprehensions
Lecture 05: Data Structures - Set and Dictionaries
Lecture 06: Classes, Objects and Constructors, Inheritance
Lecture 07: Polymorphism, Abstraction and Encapsulation
Lecture 08: Connecting to Databases, Establishing Connections to Databases, Executing SQL Queries, ORM (Object-Relational Mapping), Working with NoSQL Databases
Lecture 09: Introduction to NumPy and Pandas
Lecture 10: Introduction to Seaborn and Matplotlib
Module 02 - Statistics
Lecture 11: Introduction to Statistics, Descriptive Statistics, Sample, Population, Measures of Central Tendency, Standard Deviation
Lecture 12: Variance, Range, IQR, Outliers, Correlation, Covariance, Skewness, Kurtosis, Probability
Lecture 13: Probability, Probability Distributions, Central Limit Theorem, Binomial and Poisson Distribution
Lecture 14: Normal Distribution, Type I & Type II Error
Lecture 15: T-test, Z-test, Hypothesis Testing Interview Questions
Module 03 - SQL
Lecture 16: Basics of Database, Types of Database, Data Types, SQL Operators, Expressions, Create, Insert
Lecture 17: Drop, Truncate, Delete, Alter, Update, Select, Range, Operator, IN, Wildcard, Like, Clause
Lecture 18: Constraint, Aggregation Function, Group By, Order By, Having
Lecture 19: Joins, Case, Complex Queries, Doubt Clearing
Module 04 - Tableau
Lecture 20: Tableau Desktop, Tableau Products
Lecture 21: Data Import, Measures, Filters
Lecture 22: Data Transformation, Marks, Dual Axis
Lecture 23: Manage Worksheets, Data Visualization, Dashboarding, Project
Module 05 - Advanced Excel (Self
Paced and
Complementary)
Lecture 24: Introduction to Data Analytics, Scope of Data Analytics
Lecture 25: Microsoft Excel Overview, Basic Navigation and Usage, Cell Referencing, Formatting Excel, Advanced Formatting, Shortcuts and Basic Formulas
Lecture 26: Sorting, Filtering, Advanced Filtering, Charts, Types of Charts, Advanced Charting Techniques, and Pivot Tables (Creating, Grouping and Summarizing Data)
Lecture 27: Lookup Functions, VLOOKUP, Using VLOOKUP with Multiple Criteria, HLOOKUP, Combining HLOOKUP with Other Functions, MATCH Function, Using MATCH for Dynamic Referencing
Lecture 28: Introduction to VBA & Macros, Understanding VBA Basics, Debugging and Error Handling, Advanced VBA Techniques, Integrating VBA with Excel Functions, Designing Effective Dashboards, Building a Dashboard
Lecture 29: Understanding the Basics of Data Analysis, Data Import and Cleaning, Using Formulas and Functions, Data Visualization, Descriptive Statistics
Lecture 30: Advanced Data Analysis Techniques, DAX, Scenario and Sensitivity Analysis, Dashboards and Reports, Case Studies and Real-World Applications, Practical Examples of Data Analysis in Excel
Module 06 - Introduction to Gen AI & Huggingface Transformers Platform
Lecture 31: Introduction to AI, Hype vs. Reality, Business Applications, Ethical Considerations, Introduction to Generative AI, From Text Generation to Multimodal Models, Potential and Challenges
Lecture 32: Introduction to Open Source Huggingface Transformers Platform, Review of NLP Basics & Text Pre-processing, Introduction to NLP Concepts: Language Representations, Tokenization, Part-of-Speech Tagging, Text Preprocessing
Lecture 33: Feature Engineering: Normalization, Stemming, Lemmatization, Stop Word Removal, Understanding Key NLP Applications using Huggingface Platform
Lecture 34: Sentiment Analysis, Sentence Classification, Generating Text, Extracting an Answer from Text
Module 07 - Language Models and Transformer Models
Lecture 35: Understanding Language Models, Probability-based Language Models, Unsupervised Learning Language Representations, Introduction to Transformer Models, What are Transformer Models
Lecture 36: Types of Models: Encoder-Decoder, Decoder Only, Attention Mechanism, Tasks that Transformer Models Can Do: Translation, Text Summarization, Q&A, Text Generation, Zero Shot, Few Shot Text Classification
Module 08 - Large Language Models (LLMs)
Lecture 37: Introduction to Large Language Models (LLMs), Structure of Popular Models, Types of Models: Text to Text, Text to Image, Text to Video, Multimodal
Lecture 38: Other Types of Generative AI Algorithms: GANs (Generative Adversarial Networks), Variational Autoencoders (VAEs), Diffusion Models, Mixture of Experts, Different Models Available Currently for Image (DALL-E 2, Midjourney)
Lecture 39: Hands-on Practice of NLP Tasks Using Huggingface Library and Open-source Language Models such as Bloom for Finetuning a LLM, Zero and Few Shot Classification, Applications of Generative AI in Business
Lecture 40: Customer Insights & Sentiment Analysis, Personalized Marketing & Content Creation, Chatbots: Automating Customer Service and Support, Document Processing Automation
Lecture 41: Project Session
Data Analytics & Generative AI Program Skills Covered
Advanced Data Analysis
Python Programming
Data Visualization
Statistical Analysis
SQL Expertise
Data Visualization
Dashboard creation
Data Storytelling
Generative AI concepts
AI model training
Data Analytics & Generative AI Program Tools Covered
Data Analytics & Generative AI Program Program Benefits
Projects that you will Work On
Machine Learning
No. of Projects:10
Deep Learning
No. of Projects:10
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Job Obligation after this course
We can apply for jobs in
Build in-depth reports and dashboards with Tableau, Excel to deliver data findings efficiently across stakeholders.
Targeted at your domain experts to develop, train and deploy AI models using Generative AI for solving complex business problems.
Collect, clean, and analyze data to extract meaningful insights that inform business decisions.
Develop and tune SQL queries to maintain database performance profiling for relational databases
Use statistical and analytical methods to find trends, patterns or opportunities in your dataset.
Provide data insights to support and inform business decisions, ensuring organizations can realize their goals.
Automate routine tasks using Python to enhance efficiency and reduce manual workload.
Collaboratively partner with IT, management and other key stakeholders from cross-functional teams to implement data-driven solutions.
We gradually got trends on all our fingertips and advancements in data analytics, AI, and related technologies to maintain expertise and relevance.
Companies Hiring for this course
Program Advisors
IITs
IIMs
NITs
Experts from the IT Industries.
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.
Course Fees & Financing
Course Fees
(50% OFF upto 31ˢᵗ March)
(Inclusive Of All Taxes)
Payment Partners
We partnered with financing companies to provide competitive finance option at 0% interest rate with no hidden costs
Upcoming Batches/Program Cohorts
| Batch | Date | Time (IST) | Batch Type |
|---|---|---|---|
| Online Live Instructor Led Session | 7th Sept 2025 | 9 PM to 12 AM | Batch 1 |
| Online Live Instructor Led Session | 14th Sept 2025 | 9 PM to 12 AM | Batch 2 |
Comparison with Others
| Feature | Generative AI Program | Competitor A | Competitor B | Competitor C |
|---|---|---|---|---|
| Tools Covered | Advanced Robotics, Quantum Computing, Python, TensorFlow, and cutting-edge AI tools like GPT-4, StyleGAN, Neural Architecture Search | Primarily includes Robotic Process Automation, Python, and TensorFlow, with limited advanced AI tools | Deep Learning, Basic StyleGAN, Limited Computer Vision | Deep Learning, Computer Vision, Basic Reinforcement Learning |
| AI Focus | Intensive focus on next-gen AI technologies and applications | Basic AI concepts, with limited next-gen focus | Advanced AI techniques, Basic Computer Vision | Applied AI techniques, Advanced Computer Vision |
| Real-World Application | Innovative projects that integrate AI technologies to address cutting-edge industry challenges | Projects often focus on automation with limited AI application | Some real-world projects with a focus on computer vision | Industry-focused projects with advanced AI solutions |
| Expert-Led Instruction | Courses led by top experts in robotics, quantum computing, and AI | Instructors with a focus on automation and basic AI | Industry specialists in deep learning | Experienced AI practitioners and researchers |
| Career Opportunities | Prepares students for cutting-edge roles, including AI Researcher, Robotics Engineer, Quantum Computing Specialist, and Advanced Data Scientist | Typically prepares students for automation and basic data science roles | Provides some career advancement | Focused career paths in advanced AI fields |
| Future-Proof Skills | Cutting-edge AI and robotics skills ensuring adaptability to future technological advancements | Focuses on current technologies, with limited future-proofing | Some focus on emerging AI technologies | Advanced future technologies and AI applications |
| Cross-Industry Relevance | Skills relevant across multiple sectors, including technology, finance, healthcare, and advanced research | Skills are more niche with limited cross-industry application | Some cross-industry applications | Sector-specific expertise |
| Networking Opportunities | Extensive networking with top experts in robotics, AI, and quantum computing | Networking is typically limited to automation professionals | Some networking with AI experts | Limited networking opportunities in advanced AI fields |
| Investment Value | High return on investment due to integration of cutting-edge technologies and industry relevance | Moderate value with a focus on automation and basic data science | Provides good value for advanced AI careers | Basic investment value with a focus on specific sectors |
Data Analytics & Generative AI Program Training Faqs
Data analytics and generative AI approaches are combined in a package called Data Analytics and Generative AI. It addresses the gathering, processing, statistical analysis, deep learning, and machine learning of data. Students work on real-world projects while learning how to utilize technologies like TensorFlow, R, Python, and PyTorch. The curriculum focuses on producing fresh data and insights from massive datasets, preparing graduates for positions as machine learning specialists, AI engineers, and data analysts.
Join this course and to learn Combine data analytics with AI for insightful business solutions.
Data analytics: Methods for gathering, processing, and analyzing data are called data analytics.
Statistical Analysis: Advanced techniques for deciphering data trends are known as statistical analysis.
Machine Learning: Model building for predictions.
Generative AI: GANs and transformer models are studied in generative AI in order to produce fresh data.
Deep Learning: Analytics and generative tasks using neural networks.
Programming Language: TensorFlow, PyTorch, R, and Python are programming languages.
Data visualization: is the process of giving data meaningful visual representations.
Real-World Projects: Useful, practical undertakings.
Data analysis techniques, Advanced Excel features, data cleaning, analysis techniques, Python programming, data visualization, statistical analysis, Descriptive statistics, probability theory, Database management, SQL querying, Dashboard creation, data storytelling, Generative AI concepts, AI model training
Advanced Excel, Python, NumPy, pandas, matplotlib, SQL, Tableau/Power BI, Transformers, Hugging Face libraries, DALL-E model, OpenAI, PyTorch
A degree in Engineering, Mathematics, Science, or any equivalent field is ideal for pursuing a career in Artificial Intelligence and Data Science.
INR Fees(Exclusive of GST) : INR 144,999.00 INR Fee(Inclusive of GST) : INR 171,099.00 USD Fee: 1735(subject to be change).
After completion of this course you have opportunity on the posts:Data Analyst, AI Engineer, Machine Learning Specialist
Entry-level: 8-15 lakhs per annum
Mid-level: 15-30 lakhs per annum
Senior-level: 30+ lakhs per annum
40+ Projects done
1, we will optimise linked in profile and the algorithm of linkedin profile
2, We will conduct GITHUB and Kaggle sessions
3,We will do multiple Hackathons and guide you in problem solving skills for the interview process
4, We will ensure peer learning session are being conducted
5, We will issue mini certification for every tools.
6,We will asign you a personal mentor on pre booking i’t a one one session.
