Generative AI

Beginner to Mastery

Advanced Data Science & Generative AI with Visualization Tools

Advanced Data Science Certification

Comprehensive Data Science Program

Practical Data Science Training

Training in the latest technologies, including Generative AI.

Group Enrollment with Friends or Colleagues

Advanced Data Science & Generative AI with Visualization Tools

Course Duration

640 Hours

Next Batch

14 September 2025

Course Material

Live. Online. Interactive.

Expertise in Big Data tools like Hadoop, Spark, and NoSQL databases.

In-depth learning of visualization tools such as Tableau and Power BI.

Taught by industry professionals with extensive experience.

Prepares for a wide range of high-demand roles in data science and AI.

Highlight Advanced Data Science & Generative AI with Visualization Tools

KEY HIGHLIGHTS OF ADVANCED DATA SCIENCE & GENERATIVE AI WITH VISUALIZATION TOOLS PROGRAM

Weekly sessions with industry professionals
Dedicated Learning Management Team
640 hours of hands-on learning experience
Over 240 hours live sessions spread across 11 months
240 hours of self-paced Learning
Learn from IIT Faculty & Industry experts

More than 60+ 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 ADVANCED DATA SCIENCE & GENERATIVE AI WITH VISUALIZATION TOOLS PROGRAM?

Comprehensive Learning

Gain a broad understanding of essential data science and AI tools, from foundational skills to advanced techniques.

Real-World Application

Apply theoretical knowledge to practical projects, preparing you for real-world data challenges.

Cutting-Edge Skills

Stay ahead in the industry with training in the latest technologies like Generative AI and advanced Big Data tools.

Career Growth

Enhance your qualifications and open doors to high-demand roles in data science, AI, and Big Data.

UPCOMING BATCH:

14 September 2025

SkillzRevo Solutions

30 MINUTE MEETING

Web conferencing details provided upon confirmation.

Corporate Training, Enterprise training for teams

Batch schedule

Batch	Batch Type
Online Live Instructor Led Session	Full-Time
Online Live Instructor Led Session	Part-Time

Regional Timings

Batch	Batch Type
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

Advanced Data Science & Generative AI with Visualization Tools OVERVIEW

This Program offers a blend of theory and practice for the upcoming data scientists or AI professionals. This book covers strong basics to advance topics of Machine Learning, Deep Learning, Computer Vision and Natural Language Processing. Those participants will also gain additional expertise in data processing, visualization and Big Data technologies of all forms including an emphasis on Generative AI. This program is modeled to teach the professionals skills for utilizing modern technologies resulting in useful data-driven insights.

ENROLL NOW & BOOK YOUR SEAT AT FLAT 50% WAIVER ON FEE

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Advanced Data Science & Generative AI with Visualization Tools Objectives

This course will enable participants to have an in-depth understanding of advanced data science techniques and tools. The course aims to develop proficiency in critical areas such as Machine Learning, Deep learning, Computer Vision and NLP. They get to work on the most practical aspects of data management, more detailed and dynamic visualization as well Big Data technologies so that participants will be able to try some Generative AI solution on Advanced Problems. The goal of the course is to equip attendees with the knowledge and understanding necessary for transforming data into evidence-based insights, facilitate decision making under uncertainty; while providing key contributions towards innovative solutions across multiple domains.

Enroll Now →

Why Learn Advanced Data Science & Generative AI with Visualization Tools ?

Comprehensive Skill Development

Gain expertise in a wide range of data science and AI techniques, from foundational to advanced levels, ensuring a well-rounded skill set.

Industry-Relevant Knowledge

Stay ahead of the curve by learning the latest advancements in Machine Learning, Deep Learning, and Generative AI, all of which are highly sought after in the job market.

Hands-On Experience

Engage in practical exercises and real-world projects that enhance your ability to apply theoretical concepts to real data problems.

Data Management Mastery

Develop strong skills in data management, visualization, and Big Data technologies, enabling you to handle complex datasets and derive meaningful insights.

Versatile Career Opportunities

Open doors to various high-demand roles in data science, AI, Big Data, and analytics across multiple industries.

Cutting-Edge AI Applications

Learn to harness the power of Generative AI, a rapidly evolving field that is transforming industries and creating new opportunities for innovation.

Professional Growth

Equip yourself with the tools and knowledge to make data-driven decisions and lead impactful projects in your organization or field of expertise.

Integrated Visualization Tools

Master Tableau, Power BI, and other visualization platforms to effectively communicate insights and drive data-informed decision-making.

Program Advantages

Learn a diverse range of tools and technologies, from data science fundamentals to advanced AI, for a well-rounded education.

Gain hands-on experience with real-world datasets and projects, ensuring job readiness with practical skills in each tool.

Benefit from guidance by industry professionals, learning best practices and the latest industry standards.

Understand how tools like Machine Learning, Big Data, and Generative AI integrate to solve complex problems.

Master visualization tools like Tableau and Power BI to effectively communicate data insights.

Develop expertise in handling large-scale data with technologies like Hadoop, Spark, and NoSQL databases.

Equip yourself with in-demand skills that are valuable across various industries.

Enhance your career prospects by mastering the most sought-after tools and technologies in data science and AI.

Advanced Data Science & Generative AI with Visualization Tools program Certifications

NASSCOM

Course Completion

Project Completion

Advanced Data Science & Generative AI with Visualization Tools Curriculum

Lecture 01: Introduction to Python

Lecture 02: Operators and Conditional Statements

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

Lecture 09: Introduction to Numpy and Pandas

Lecture 10: Introduction to Seaborn and Matplotlib

Lecture 11: Introduction to Statistics, Descriptive Statistics, Sample, Population, Major 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

Lecture 16: Introduction to ML, Types of variables, Encoding, Normalization, Standardization, Types of ML, Linear Regression

Lecture 17: Linear Regression, Logistic Regression, SVM, KNN, Naïve Bayes, Decision Tree, Random Forest

Lecture 18: Mean Absolute Error, Mean and Root Mean Square Error, Confusion Matrix, R2 Score, Adjusted R2 Score, F1 Score

Lecture 19: Classification Report, AUC ROC, Accuracy, Ensemble Techniques, Random Forest, Xgboost

Lecture 20: Unsupervised Machine Learning, PCA, Clustering, k-Means Clustering and Hierarchical clustering

Lecture 21: Introduction to Neural Network, Forward Propagation, Activation Function

Lecture 22: Activation Function (Linear, Sigmoid, Relu, Leaky Relu), Optimizers, Gradient Descent, Stochastic Gradient Descent

Lecture 23: Mini Batch Gradient Descent, Adagrad, Padding, Pooling, Convolution

Lecture 24: Checkpoints and Neural Networks Implementation and Introduction to Time Series Analysis

Lecture 25: Various components of the TSA, Decomposition Method (Additive Method and Multiplicative)

Lecture 26: ARMA and ARIMA

Lecture 27: Basic of Database, Types of Database, Data Types, SQL Operators, Expression, Create, Insert

Lecture 28: Drop, Truncate, Delete, Alter, Update, Select, Range, Operator, IN, Wildcard, Like, Clause

Lecture 29: Constraint, Aggregation Function, Group by, Order by, Having

Lecture 30: Joins, Case, Complex Queries, Doubt Clearing

Lecture 31: Tableau Desktop, Tableau products

Lecture 32: Data import, Measures, Filters

Lecture 33: Data transformation, Marks, Dual Axis

Lecture 34: Manage worksheets, Data visualization, Dashboarding, Project

Lecture 35: Power BI Platform, Process Flow

Lecture 36: Features, Dataset, Bins

Lecture 37: Pivoting, Query Group, DAX Function

Lecture 38: Formula, Charts, Reports, Dashboards

Lecture 39: Bookmarks and Buttons, Conditional Formatting and Sorting, and Report Layout and Interaction

Lecture 40: Tabular Visuals, Modelling and Calculations, Advanced Data Modelling Scenarios and DAX in Power BI

Lecture 41: Introduction, SQL vs NoSQL, Data Model, Data types, Object ID, Data type, Binary Data, Date, Null, Boolean, Integer, String

Lecture 42: Collection method, queries, CRUD Operation, Insert, Find, Update, Delete, Validate, Bulk write, Delete one

Lecture 43: Introduction to Java, Installation, Syntax main()/printIn()/print()/ Variable [String, Int, Boolean, float, char], Datatypes, Operators

Lecture 44: Conditions, Loop, Methods, Class, File Handling

Lecture 45: Types of Data, Introduction to Big Data (History, V's of Big Data, Advantages & Disadvantages of Big Data), Big Data Applications in Various Sectors, Introduction to Hadoop, Scaling (Horizontal and Vertical), Challenges in Scaling, Parallel Computing, Distributed Computing and Hadoop, Hadoop Tools Overview, Big Data Analytics Lifecycle

Lecture 46: On-Premises Installation Oracle Virtual Box and setup of VM & Ubuntu, Basic Linux command, Download and Installation of Hadoop, Introduction to Hadoop, Core components of Hadoop, Hadoop working, Principle

Lecture 47: VM creation on Cloud (AZURE), Configuration & Insight to Single Node Hadoop Deployment (bsshrc, hadoop-env, core-site, hdfs-site, mapred-site, yarn-site), Format HDFS Namenode.

Lecture 48: HDFS Architecture, Hadoop Commands and Implementation

Lecture 49: MapReduce, MapReduce Implementation

Lecture 50: Introduction to Hive, Hive Installation, Hive Implementation

Lecture 51: Hive Query Language, SQL Operations

Lecture 52: HIVE_SQL Operations

Lecture 53: Installation of Spark, PySpark, Introduction to Sqoop, Installation of Sqoop

Lecture 54: PySpark Query, Installation of HBase, HBase Query

Lecture 55: PIG Installation and Query

Lecture 56: PIG Query, Oozie

Lecture 57: Flume and Doubt Clear

Lecture 58: Introduction to Image Processing, Feature Detection, OpenCV

Lecture 59: Convolution, Padding, Pooling & its Mechanisms

Lecture 60: Forward Propagation & Backward Propagation for CNN

Lecture 61: CNN Architectures like AlexNet, VGGNet, InceptionNet, ResNet, Transfer Learning

Lecture 62: Introduction to Text Mining, Text Processing using Python and Introduction to NLTK

Lecture 63: Sentiment Analysis, Topic Modeling (LDA) and Named Entity Recognition

Lecture 64: BERT (Bidirectional Encoder Representations from Transformers), Text Segmentation, Text Mining, Text Classification

Lecture 65: Automatic Speech Recognition, Introduction to Web Scraping

Lecture 66: RL Framework, Component of RL Framework, Examples of Systems

Lecture 67: Types of RL Systems, Q-Learning

Lecture 68: Introduction to AI, Hype vs. Reality, Business Applications, Ethical Considerations, Introduction to Generative AI, From Text Generation to Multimodal Models, Potential and Challenges

Lecture 69: 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 70: Feature Engineering: Normalization, Stemming, Lemmatization, Stop Word Removal, Understanding Key NLP Applications Using Huggingface Platform

Lecture 71: Sentiment Analysis, Sentence Classification, Generating Text, Extracting an Answer from Text

Lecture 72: Understanding language models, Probability-based language models, Unsupervised learning language representations, Introduction to transformer models, What are transformer models

Lecture 73: 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

Lecture 74: Other types of Generative AI algorithms, - GANs ( Generative Adverserial Networks), Variational Autoencoders (VAEs), Diffusion Models, Mixture of Experts, - Diffferent models available currently for image ( DALLE-2, Midjourney)

Lecture 75: Other types of Generative AI algorithms, - GANs ( Generative Adverserial Networks), Variational Autoencoders (VAEs), Diffusion Models, Mixture of Experts, - Diffferent models available currently for image ( DALLE-2, Midjourney)

Lecture 76: Hands on practice of NLP tasks using Huggingface library and opensource language models such as Bloom for finetuning a LLM, zero and few shot classification,-Applications of Generative AI in business

Lecture 77: Customer Insights & Sentiment Analysis- Personalized Marketing & Content Creation- Chatbots: Automating Customer Service and Support- Document Processing Automation

Lecture 78:Langchain, Applied use case for Gen AI – hands on exercise- Designing a custom chatbot- Data analytics using Gen AI model such as OpenAI API

Lecture 79: AI Application Stack: Infrastructure & foundation layer- Overview of AI infrastructure: cloud platforms, GPU, and distributed computing, Setting up an AI environment for generative models- Infrastructure considerations for scalable AI applications- Retrieval augmentation generation or RAG

Lecture 80: Hallucination, Data Privacy, Ethics, and Environmental Impact of AI & future of Work- Importance of data privacy in AI applications- Ethical considerations in AI development and Deployment- Environmental Impact and Sustainability in AI- The Future of Work: How AI Will Reshape Roles and Responsibilities

Lecture 81: Project Discussion session

Advanced Data Science & Generative AI with Visualization Tools Skills Covered

Proficiency in Programming

Statistical Analysis

Advanced Machine Learning Techniques

Deep Learning and AI Techniques

Computer Vision Techniques

Natural Language Processing Techniques

Reinforcement Learning Techniques

Advanced Data Analysis in Excel

Data Analysis and Visualization

SQL querying

NoSQL Database Management

Big Data Management

Hadoop ecosystem tools

Spark Data Processing and Analytics

Transformer architectures Language Modeling

Generative Pre-trained Transformers (GPT)

Image Generation

Large-scale image synthesis

Generative Adversarial Networks (GANs)

Retrieval-Augmented Generation (RAG)

Advanced Data Science & Generative AI with Visualization Tools Tools Covered

Advanced Data Science & Generative AI with Visualization Tools Program Benefits

CAREER OPPORTUNITIES AFTER THIS COURSE

AI Product Manager Salary Range

Min

$100,000

Average

$145,000

Max

$190,000

MASTER GANS, TRANSFORMERS & DEEP LEARNING WITH REAL PROJECTS

Practice Essential Tools

Get Real-world Experience

Machine Learning

NO. OF PROJECTS: 10

Deep Learning

NO. OF PROJECTS: 10

Generative AI

NO. OF PROJECTS: 8

Capstone Projects of this Program

Multimodal Text-to-Image Generator

A system that creates high-quality, realistic images from descriptive text inputs, blending multiple data types for creative visual output.

AI Music Composer with Genre Adaptation

An AI tool that generates original musical compositions while adapting to specific genre styles, tempo, and mood preferences.

Realistic Deepfake Video Synthesizer

A tool that realistically manipulates and synthesizes video content to create authentic-looking deepfake footage for various applications.

Personality-Driven Conversational AI Assistant

A chatbot designed to interact with a distinct and consistent personality, providing a more natural and engaging user experience.

Artistic Style Transfer Engine for Videos

A program that applies the artistic style of a source image to every frame of a video, creating a new, stylized visual experience.

Context-Aware Text Summarization System

An advanced system that generates concise summaries of long texts by understanding the document's broader context and key information.

Voice Cloning and Speech Style Transfer Tool

A tool that replicates a speaker's voice and transfers a specific speech style or emotion to new synthesized audio content.

Interactive AI Storyteller with Image Generation

An AI that collaboratively creates stories with users, dynamically generating scenes and characters based on a developing narrative.

2D Sketch to 3D Object Generation Pipeline

A seamless workflow that converts simple two-dimensional sketches into detailed, three-dimensional models for creative and design purposes.

Synthetic Data Generator for Model Training

A system that produces large and diverse datasets for machine learning models, overcoming data scarcity for effective training.

AI-Powered Video Subtitle Generator and Translator

An automated solution that transcribes spoken language in videos and translates it into accurate subtitles for global accessibility.

Generative Design Tool for Product Prototyping

An AI application that rapidly generates numerous product design prototypes based on a set of constraints and functional requirements.

RAG-based Research Assistant (Retrieval-Augmented Generation)

An intelligent assistant that answers complex queries by retrieving relevant information from large documents and generating coherent responses.

Multilingual Chatbot with Memory and Personality

A conversational agent that can communicate in multiple languages while maintaining a consistent personality and recalling past interactions.

AI-Powered Comic Strip Generator from Text Prompts

A tool that creates unique comic strips by converting user text prompts into sequential images with a consistent artistic style.

Explainable AI Engine for Text Classification

An AI system that classifies text and provides clear, understandable reasons for its decisions, ensuring transparency and trust.

Autonomous Slide Generator from Research Papers

An AI that automatically extracts key findings and data from research papers to create well-structured, presentable slide decks.

AI Assistant for Code Generation and Explanation

A helpful tool that writes code snippets and explains complex programming logic in simple terms, assisting developers with their tasks.

AI-Driven Marketing Content Generator Across Formats (text, image, video)

A unified platform that produces marketing materials in various formats, including text, images, and videos, from a single campaign brief.

Real-Time Emotion Detection and Response AI System

A system that identifies human emotions from facial expressions or speech and generates appropriate, empathetic responses in real time.

Job Obligation After This Course

WE CAN APPLY FOR JOBS IN

Analyze large datasets to identify trends, patterns, and insights to inform business decisions.

Design, develop, and deploy machine learning and AI models to solve specific problems.

Manage and maintain data pipelines, ensuring data quality and integrity across systems.

Develop and present data visualizations and reports to communicate findings effectively.

Implement and optimize algorithms for machine learning, deep learning, and AI applications.

Work with other departments to understand data needs and provide analytical support.

Integrate various data science and AI tools to create comprehensive solutions for complex problems.

Address and resolve data-related challenges and issues that arise in projects or operations.

Stay updated with the latest advancements in data science, AI, and related technologies.

Document processes, models, and findings to ensure reproducibility and clarity in your work.

Companies Hiring for this Course

Admission Process

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

Enroll Now & Save Up To

60%

In USD

$2999

In INR

₹262000

Inclusive of All Taxes

Enroll Now →

Payment Partners

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

UPCOMING BATCHES/PROGRAM COHORTS

Batch	Date	Time (IST)	Batch Type
Online Live Instructor Led Session	30 August 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	Our Course	COMPETITOR A	COMPETITOR B
Comprehensive Coverage	Extensive range including data science, AI, Big Data, and visualization tools	May focus on narrower set of tools or specific domains	General AI, Big Data, and visualization tools
Hands-On Experience	Emphasis on practical projects and real-world datasets	May offer limited practical experience or fewer projects	Hands-on projects mainly in traditional AI
Cutting-Edge Technologies	Includes the latest advancements like Generative AI	May not cover the latest technologies or focus on older tools	Basic tools covered
Big Data Tools	Covers Hadoop, Spark, NoSQL, MongoDB	May not include all Big Data tools or have limited coverage	Basic Big data tools
Visualization Tools	Extensive training in Tableau and Power BI	May focus on one visualization tool or offer less depth	Basic tools knowledge
Expert Instruction	Led by industry professionals with deep experience	May vary in instructor experience and industry relevance	University Instructors
Career Advancement	Prepares for a wide range of high-demand roles	May have a narrower focus or fewer career opportunities	No opportunities
Program Flexibility	Suitable for beginners to experienced professionals	May be tailored to specific experience levels or needs	May be tailored to specific experience levels or needs

Advanced Data Science & Generative AI with Visualization Tools

Course Duration

Next Batch

Course Material

KEY HIGHLIGHTS OF ADVANCED DATA SCIENCE & GENERATIVE AI WITH VISUALIZATION TOOLS PROGRAM

WHY JOIN ADVANCED DATA SCIENCE & GENERATIVE AI WITH VISUALIZATION TOOLS PROGRAM?

Comprehensive Learning

Real-World Application

Cutting-Edge Skills

Career Growth

UPCOMING BATCH:

SkillzRevo Solutions

Batch schedule

Regional Timings

Advanced Data Science & Generative AI with Visualization Tools OVERVIEW

Advanced Data Science & Generative AI with Visualization Tools Objectives

Why Learn Advanced Data Science & Generative AI with Visualization Tools ?

Comprehensive Skill Development

Industry-Relevant Knowledge

Hands-On Experience

Data Management Mastery

Versatile Career Opportunities

Cutting-Edge AI Applications

Professional Growth

Integrated Visualization Tools

Program Advantages

Advanced Data Science & Generative AI with Visualization Tools program Certifications

NASSCOM

Course Completion

Project Completion

Advanced Data Science & Generative AI with Visualization Tools Curriculum

Advanced Data Science & Generative AI with Visualization Tools Skills Covered

Advanced Data Science & Generative AI with Visualization Tools Tools Covered

Advanced Data Science & Generative AI with Visualization Tools Program Benefits

CAREER OPPORTUNITIES AFTER THIS COURSE

AI Product Manager Salary Range

MASTER GANS, TRANSFORMERS & DEEP LEARNING WITH REAL PROJECTS

Capstone Projects of this Program

Job Obligation After This Course

Companies Hiring for this Course

Admission Process

Course Fees & Financing

UPCOMING BATCHES/PROGRAM COHORTS

COMPARISON WITH OTHERS

Frequently Asked Questions