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In today’s technology-first world, Data Science empowers businesses to uncover patterns, predict outcomes, and solve complex challenges with speed and accuracy.
At Itvedant, our comprehensive Data Science program is crafted to build deep expertise through hands-on learning over 6-8 months. With 80% practical training, 30+ case studies, and industry-modeled projects, you'll gain future-ready skills that equip you for in-demand tech roles.
Explore each topic in depth through interactive sessions, real-world use cases, and hands-on tools. Gain a strong understanding of concepts while building practical skills that matter in real-world roles.
Case Studies & Projects
Languages & Tools
Live Sessions Hours
Python fundamentals and data types
Operators and decision control structures
Loop control structures
Collection data types (List, Tuple, Set, Dictionary, String)
Functions, modules, and lambda expressions
Object-oriented programming (classes, inheritance, polymorphism)
File handling and exception handling
API fundamentals and HTTP methods
Consuming external APIs and working with JSON
Building endpoints using FastAPI
AI Advantage
Debug runtime and logic errors faster with ChatGPT
Generate test cases for fare calculation, seat allocation and booking edge cases with AI
Refactor procedural code into functions, modules and OOP classes using Claude
Create AI-suggested test scenarios for API endpoints
Machine learning lifecycle and business problem formulation
Data preprocessing pipelines and data leakage prevention
Regression modeling for interest rate prediction
Classification modeling for loan default prediction
Ensemble learning with Random Forest and feature importance
Model evaluation, overfitting control and hyperparameter tuning
Experiment tracking, model versioning and model registry
Model serving through REST APIs
Containerization and cloud deployment
CI/CD automation and automated testing
Production monitoring, data drift detection and model retraining
AI Advantage
Design feature engineering and preprocessing pipelines with AI guidance
Get AI-recommended hyperparameter search spaces for GridSearchCV
Generate pytest test cases, Dockerfiles and GitHub Actions workflows using Claude
Interpret model metrics and results with ChatGPT
Machine Learning fundamentals and algorithm types
Overfitting, underfitting, and model evaluation
Deep Learning and neural network basics
Activation functions, forward/backpropagation, gradient descent
NLP text preprocessing and text representation techniques
Word embeddings (Word2Vec, GloVe)
Sequence models (RNN, LSTM, GRU) and their limitations
Transformer architecture, self-attention, and multi-head attention
Encoder-decoder models and BERT vs GPT
LLM fundamentals, training, tokens, and context windows
AI Advantage
Using pretrained LLMs like ChatGPT & Claude to benchmark against custom-built models
Diagnose and fix neural network training issues with AI-guided explanations
Compare model performance across ML, DL and transformer approaches with AI-generated insights
Prompt fundamentals and design principles
Zero-shot, one-shot, and few-shot prompting
Role-based and persona prompting
Structured prompts and JSON output
Reflection prompting
Prompt injection, guardrails, and evaluation
LCEL and Runnables
Output parsers
Chat history and memory in LangChain
Tokens, tokenization, and context window
Input and output token usage
Prompt optimization and context compression
Model selection and cost estimation
AI Advantage
Draft, refine and A/B test zero-shot, one-shot and few-shot prompts using ChatGPT
Analyse token usage, compress prompts and estimate costs across model tiers with AI
Debug LCEL chains, output parsing errors and agent behaviour with Gemini
RAG fundamentals and RAG vs prompt engineering vs fine-tuning
RAG architecture, workflow, and use cases
Types of RAG (Naive, Advanced, Modular)
Data ingestion from multiple sources
Document loaders, text extraction, and cleaning
Chunking strategies (fixed-size, recursive, semantic, sentence-based)
Chunk size, overlap, and metadata-based filtering
Embeddings and semantic similarity (cosine similarity, distance metrics)
Word vs sentence/document embeddings, multilingual embeddings
Vector databases and vector indexing
Similarity search, Top-K retrieval, and metadata filtering
Comparison of vector databases (ChromaDB, FAISS, Pinecone, Weaviate, Qdrant, Milvus)
AI Advantage
Choose the right chunking strategy and embedding model with AI-driven recommendations.
Evaluate retrieval quality and relevance scores using Gemini.
Troubleshoot vector search and retrieval pipeline issues with Claude.
Agent reasoning loop and ReAct pattern (Thought, Action, Observation)
Agent memory, state, and error handling
Function/tool calling, schemas, and structured outputs
Agent decision-making: routing, intent classification, tool selection
Frontend development with Streamlit (UI components, chat interface, session state, file upload)
Connecting frontend and backend using FastAPI and REST APIs
Streaming responses and error handling across the stack
MCP architecture: client/server, resources, tools, prompts
Building MCP servers and connecting agents to MCP
Production deployment: environment variables, Docker, logging, security, monitoring
AI Advantage
Generate tool schemas and function definitions using Claude
Debug agent reasoning loops and tool call failures with Gemini
Review deployment configuration and security practices with AI-powered checks
Prompting vs RAG vs Fine-Tuning tradeoffs
Cost and data considerations for fine-tuning
Full fine-tuning vs Parameter-Efficient Fine-Tuning (PEFT)
Instruction tuning / Supervised Fine-Tuning (SFT)
Open-source vs closed-source model fine-tuning
LoRA and QLoRA techniques
Hugging Face PEFT library
Fine-tuning dataset structure and preparation
Data quality vs data quantity, cleaning and formatting for SFT
Hands-on fine-tuning with hyperparameter tuning (learning rate, epochs, batch size)
Before/after performance evaluation
Serving fine-tuned models (Hugging Face Inference, Ollama)
AI Advantage
Convert raw ATC transcripts into SFT-ready instruction/input/output format using ChatGPT
Clean, filter and de-duplicate training data with AI for higher-quality datasets
Evaluate before/after fine-tuning performance with Claude as a second reviewer
Responsible AI principles: fairness, transparency, privacy, safety, accountability
Human-in-the-loop and explainability
Responsible AI lifecycle and risk identification
Sources and types of LLM bias, bias testing and mitigation
Fairness vs accuracy tradeoffs
Hallucinations: causes, detection, and grounding via RAG
Input/output guardrails and content safety
Prompt injection and jailbreak awareness
Output validation and LLM evaluation
PII, data leakage, and data minimization
Data governance and anonymization
Agent permissions, tool access, and human approval workflows
Responsible AI risk assessment framework (Identify → Assess → Mitigate → Validate → Monitor)
AI Advantage
Produce structured risk assessment reports with Claude
Detect hallucinations by cross-checking answers against trusted sources using ChatGPT
Draft data handling policies with AI support
Real-World Impact: How Leading Companies Use Data Science to Innovate, Predict & Scale
Hurry and grab your seat in Itvedant’s Data Science with ML & Agentic AI course.
With the global Data Science market expected to surpass $730 billion by 2030, skilled data scientists are at the forefront of solving real-world problems across every industry.
Itvedant’s practical, real-world training ensures you are prepared to seize opportunities in a tech-driven world.
AI - Powered
Every Lecture is
One-Click Job
Self Learning Hub
Track Your Daily
Live Corporate
Internship Manager
AI- Powered
Every Lecture Is Just
One-Click Job
Easily Shareable
Easily Verified
Enhance Credibility
14.5 Lacs
7.5 LPA
6.2 LPA
6 LPA
5.3 LPA
5 LPA
5 LPA
5 LPA
4.6 LPA
Pan India Placements
80% Practical Training
Industry Recognized Certifications
Integrated Internship
Personalised Career Coach
1:1 Doubt Resolution Support
Alumni Network
Multi-Industry Interview Preparation
Profile Building Session
2Nfinity Drive
Andheri Branch
Axio Virtual Drive
Bangalore Branch
Godrej Infotech Drive
Andheri Branch
Bajaj Alliance Drive
Delhi Branch
Pre-Placement Pep Talk
Delhi Branch
Amity Software Drive
Delhi Branch
Ahy Consulting Drive
Thane Branch
Aroha Technologies
Bangalore Branch
3Minds Digital Drive
Thane BranchAt Itvedant, we offer a structured program that equips you with the necessary skills to succeed in this field. Check out the details below to see if this course aligns with your goals:
| Criteria | Details |
|---|---|
| Ideal Candidates | - Analytical Thinkers: Individuals excited to build models and solve complex business challenges. - Career Switchers: Professionals seeking transition into AI, ML, or Data roles. - Non-Coders: Beginners ready to explore Python and data science. - Business Professionals: Individuals seeking to enhance decision-making through data insights. |
| Course Highlights | - Comprehensive Curriculum: Covers Python, SQL, ML, Deep Learning, and AI tools. - Practical Training: 80% practical focus through hands-on data science projects. - Industry Experts: Learn from professionals with extensive field experience. - Flexible Learning Modes: Both classroom and online options are available. |
| Career Prospects | - High Demand: Job roles include Data Scientist, ML Engineer, and AI Developer. - Competitive Salaries: One of the top-paying domains in the tech industry. - Growth Opportunities: Rapid growth across BFSI, healthcare, retail, and tech. |
| Unlimited Interview Opportunities | - Comprehensive Curriculum: Step-by-step career support from mock interviews to profile building. - Capstone & Domain Projects: EBuild strong portfolios with real-world datasets. - Comprehensive Support: From instant doubt-solving sessions to career guidance. |
Data Science is one of the fastest-growing and most impactful tech fields in 2026, as companies across industries rely on data for decision-making. Here’s why learning Data Science is a smart career move:
Yes! Itvedant provides comprehensive, industry-relevant training designed to make you a skilled Data Scientist professional. Our structured program covers everything you need to master data science, from fundamental concepts to advanced techniques.
No, Data Science is not difficult to learn when guided through a structured curriculum and real-world training. While it may seem technical, a logical mindset and problem-solving approach are more important than advanced coding skills initially.
Learners can begin with Python, Excel, and SQL, which are beginner-friendly tools, before progressing to Machine Learning, Data Visualization, and AI models. With consistent practice, hands-on projects, and mentorship, anyone can build proficiency in Data Science.
At Itvedant, we combine expert-led training, project-based learning, and dedicated placement support, enabling both freshers and professionals to confidently pursue a Data Science career.
Data Science is the field of extracting knowledge and insights from structured and unstructured data using scientific methods, algorithms, and advanced analytics. It integrates tools like Python, SQL, Excel, Machine Learning, and AI to build predictive models, automate decisions, and uncover patterns.
These capabilities enable businesses to solve complex problems, forecast trends, personalize customer experiences, and drive data-informed strategies.
To learn Data Science effectively, it’s best to join a structured program that blends theoretical foundations with hands-on practice. Our industry-ready Data Science Course is crafted to build expertise in data processing, model building, and machine learning
With real datasets, AI-driven case studies, and continuous mentorship, learners gain the practical knowledge required to solve complex problems and thrive in data-driven roles.
Our Data Science Training Program is a comprehensive course that covers Python, SQL, and Excel, along with advanced modules in machine learning, deep learning, and AI. It also includes training in data visualization with tools like Tableau and real-world model deployment.
You'll build your portfolio through live projects and a capstone project. We also provide end-to-end interview prep and placement support to help you succeed in roles such as Data Scientist, AI Engineer, or ML Developer.
Our Data Science Course fees are structured to be affordable for learners and professionals. We offer flexible payment options and EMI plans to make learning accessible. The fee includes course certification, access to industry-standard tools, hands-on projects and case studies, and dedicated placement assistance to help you transition into a data-focused career
Yes, absolutely. Our Data Science Training begins with Python, SQL, and data handling fundamentals, making it ideal for beginners, career changers, and freshers. No prior coding experience is required, just curiosity and a passion for solving problems with data. The course is structured to take you from the basics to building machine learning and AI models, step by step.
Itvedant stands out as a leading Data Science Institute because we offer modern classroom infrastructure, certified trainers with real industry experience, and a curriculum that aligns with current job market demands. Our one-on-one mentorship ensures personalized guidance, while our hands-on training model prepares you for high-paying roles in the field of data science.
Our Data Science Classes follow a blended format that includes live online sessions, classroom-based training, and project-driven practical work. You’ll explore real-world datasets using tools like Python, SQL, Excel, and machine learning libraries. Doubt-solving sessions and mentor support ensure personalized learning and concept clarity.
Yes, you can take our Data Science Classes online from anywhere in the world. The online format includes live interactive sessions with expert instructors, lifetime access to recorded materials, and personalized one-on-one mentorship. With this flexibility, you can learn at your own pace without compromising on the quality of instruction.
Our Data Science course provides comprehensive career support to help you enter the tech industry confidently. We guide you through resume building, LinkedIn optimization, and mock interviews with domain experts. We also conduct placement drives and connect you with top recruiters hiring for roles like Data Scientist, AI/ML Engineer, and Data Engineer.
Yes, Itvedant’s Data Science Course is designed for beginners and welcomes students from both technical and non-technical backgrounds. The curriculum starts with Python basics, data handling, and statistics, ensuring that even without prior coding or STEM experience, you can pursue a successful career in data science.
These courses are intended for anyone interested in learning Python Full Stack Development or data science.
Itvedant, with 19+ branches across India, provides flexible learning options through both classroom and online courses. Whether you prefer the interactive experience of offline classes or the convenience of online learning, Itvedant ensures quality education tailored to your needs.
The Data Science with ML & Agentic AI course is highly recommended if you want to become a Data Scientist. This course covers essential topics such as Python programming, machine learning, deep learning, statistical analysis, big data technologies, and data visualisation. By mastering these skills, you can work on predictive modelling, AI-driven solutions, and advanced analytics to extract valuable insights from data.
Yes, Python is covered from scratch in both of our courses.
The courses are a mix of live training and recorded video lectures, interactive quizzes, and assignments.
The duration of the data science course with ML & Agentic AI is 6 Months.
You do not need any prior coding knowledge to apply to this course.
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