Data Science and AI Course in Pune
Technogeeks X AI industry-aligned Data Science and AI Course in Pune take you from foundational mathematics and Python programming to production-grade machine learning and generative artificial intelligence
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Why Choose an Integrated Artificial Intelligence and Data Science Course?
Technogeeks X AI Artificial Intelligence and Data Science Course in Pune contains data analysis, Python, machine learning, AI, and Generative AI in one career-focused data science program. Through this data science training with placement assistance learners will build practical skills, they work on real-world projects, also candidates get job openings for applying roles such as Data Scientist, AI Engineer, ML Engineer, and Data Analyst.
Bridging the Gap Between Data Science, Machine Learning, and Generative AI
This data science and artificial intelligence course bind together concepts like Data Science, Machine Learning, Artificial Intelligence, and Generative AI. Learners get theoretical as well as practical skills in Python, data analysis, ML algorithms, deep learning, LLMs, and AI tools . Candidates also learn how to build real-world AI solutions and you will get ready for modern careers in Data Science and AI.
One Connected AI & DS Program Designed for Industry Outcomes
Learn how actual data, machine learning, and AI work together in real world business applications. This AI driven data science training in pune at Technogeeks X AI will help you build skills in Python, data analysis, ML, Generative AI, and AI automation which companies require nowadays. Learners move from concepts to practical industry projects.
From raw data to model in production
Every project in this course follows the same pipeline a working data scientist uses on the job.
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01
Raw Data
CSV · Database · APIs
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02
Clean
Pandas · NumPy · SQL
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03
Explore
EDA · Statistics · Visualization
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04
Model
Scikit-learn · ML Algorithms
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05
Evaluate
Metrics · Validation
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06
Deploy
Model deployment & monitoring
Comprehensive AI and Data Science Course Syllabus
The full syllabus is grouped into six learning phases so it's easier to see how everything fits together.
- Python Programming Basics & IDE Setup
- Data Structures (Lists, Tuples, Dictionaries, Sets)
- Control Flow, Loops & List Comprehensions
- Functions, Lambda, Map/Filter, Args & Kwargs
- File Handling & Exception Handling
- Object-Oriented Programming (Classes, Inheritance, Polymorphism)
- Advanced Python Modules (Decorators, Generators, Regex, Datetime)
- Multithreading & Multiprocessing
- SQL Fundamentals & Python-SQL Integration
- Statistics & Mathematics for Data Science
- Introduction to NumPy Arrays
- NumPy Indexing, Selection & Operations
- Introduction to Pandas Series & DataFrames
- Handling Missing Data
- Groupby & Data Aggregation
- Data Input & Output Operations
- Excel Integration with Pandas
- Text Data Mining & Processing
- Introduction to Data Analysis
- Advanced Excel (Data Cleaning, Pivot Tables, Conditional Formatting)
- Data Visualization & Dashboarding using Excel
- Data Visualization with Matplotlib
- Plotting with Object-Oriented Approach & Subplots
- Data Visualization using Power BI
- Building Reports & Dashboards in Power BI
- Types of Graphs & Multiple Graph Combinations
- Introduction to Machine Learning (Supervised & Unsupervised)
- Linear Regression with Python
- K-Nearest Neighbours (KNN)
- Decision Tree & Random Forest
- Support Vector Machines (SVM)
- Principal Component Analysis (PCA)
- K-Means Clustering
- Hierarchical Clustering
- Association Rule Mining (Apriori)
- Model Evaluation, Bias-Variance Trade-off & CAP Curve Analysis
- Introduction to Natural Language Processing
- NLTK Library, Stemming & Data Vectorization
- Sentiment Analysis Project (Customer Reviews)
- Neural Networks & Deep Learning Basics
- TensorFlow Installation & Basics
- Keras Basics & Pipeline Implementation
- MNIST Digit Classification Project
- Introduction to Generative AI & Foundation Models
- Transformer Architecture, Tokenization & Embeddings
- Building LLM Applications with Python
- Retrieval-Augmented Generation (RAG) & Vector Databases
- Building Apps with LangChain
- Prompt Engineering (Zero-shot, Few-shot, Chain-of-Thought)
- Responsible AI Use
- Major Capstone Project
- Version Control & GitHub for Project Management
AI, ML & Data Science: Career Opportunities and Roles
In these data data science training with gen ai tools, you can target job roles such as :
| Data & Analytics Roles | AI & ML Roles | Advanced AI Roles |
|---|---|---|
| Data Analyst | AI Engineer | Generative AI Engineer |
| Data Scientist | Machine Learning Engineer | LLM Engineer |
| Data Engineer | AI/ML Developer | NLP Engineer |
| Business Analyst | Deep Learning Engineer | Computer Vision Engineer |
| Data Visualization Analyst | Applied AI Engineer | AI Automation Engineer |
| Product Data Analyst | Robotics AI Engineer | Prompt Engineer |
| Data Quality Analyst | Research Scientist – AI/ML | AI Application Developer |
Data Scientist vs. AI Engineer vs. Machine Learning Engineer
| Main Point | Data Scientist | AI Engineer | Machine Learning Engineer |
|---|---|---|---|
| 1. Main Focus | They use data, work on it, find insight and solve real problems which real businesses are facing. | AI Engineer work is like building AI applications, also generative AI applications and AI agents. | Main work is like building and improving machine learning models. |
| 2. Key Skills | Python, SQL, statistics, data analysis, visualization, and machine learning. | Python, AI, LLMs, Generative AI, RAG, APIs, and AI agents. | Python, ML algorithms, Scikit-learn, TensorFlow, PyTorch, and MLOps. |
| 3. Main Work | Data gets collected, cleaned, analysed and studied to make predictions. | AI-powered applications get developed and business tasks get automated. | Machine learning models get trained, tested and improved. |
| 4. Common Projects | Sales prediction, customer segmentation, fraud detection, and predictive analytics. | AI chatbots, document Q&A, AI agents, recommendation assistants, and automation. | Classification, regression, forecasting, recommendation, and image recognition. |
| 6. Learning Path | A Data Science Course in Pune can build skills in Python, SQL, statistics, ML, and data science projects. | An AI-focused data science program can help learners develop Generative AI and AI engineering skills. | A Machine Learning Course in Pune or data science training can help build machine learning model development and deployment skills. |
Difference between DS, AI and ML
| Concept | What It Is | Primary Goal | Core Focus / Method | Real-World Business Example |
|---|---|---|---|---|
| Data Science (DS) | Its full lifecycle where data is gathered, gets cleaned and analysed for finding useful insight. | You will get actionable insights and answer "What happened and why?" | Statistics, data cleaning, exploratory data analysis, data visualization, business intelligence. | Analyzing past sales data to find which products sold best last year. Past sale data get analysed, to find which product got sold last year. |
| Machine Learning (ML) | Its subfield of AI (and the algorithmic engine inside Data Science) that learns continuously from data patterns. | Accurate automated prediction done on unseen data. | Training statistical algorithms (e.g., decision trees, regression, neural networks) on past data. | Predicting which products a particular customer is likely to buy next month. |
| Artificial Intelligence (AI) | Its broad umbrella of computer science aimed at creating intelligent, autonomous systems. | Simulate human-like decision-making, reasoning, and problem-solving. | Generative AI, natural language processing (NLP), computer vision, deep learning, automated agents. | An AI shopping assistant that answers questions asked by customers and recommends products in real time. |
| Why Learn Both? | Combination of Data Science and AI gives you an end-to-end skillset-from analysis to automation. | Moving from studying past data to building smart AI systems that can learn itself and make decisions on their own. | Collecting data , making decisions, and building AI agents for real-world use. | Finding those customers who may leave and with the help of AI automatically sending them offers or messages to keep them. |
Get an Industry-Recognized Certificate
A certificate that reflects real project work, not just seat time.
Learn Data Science with AI & ML.
Build practical skills in data science, machine learning, and AI with real-world projects and AI-powered tools.
Where this course takes you
Learn
Python, Statistics, Machine Learning fundamentals and Deep Learning basics.
Build
Apply every module to a real, messy dataset.
Portfolio
Ship 3–4 machine learning case studies you can show off.
Interview
Mock interviews built around your own projects.
Apply
Apply for roles with mentor and profile support.
Why Choose Technogeeks for Data Science and AI Course
Resume / CV
Data science-focused resume built around your projects.
Mock Interviews
Practice rounds with real interview feedback.
Interview Prep
Common data science and ML interview questions, solved.
Mentorship
Ongoing guidance from working data professionals.
Job Assistance
Access to relevant openings and referrals.
Profile Guidance
LinkedIn and portfolio review before you apply.
Alumni Working Across the Industry
A growing network of data scientists who started exactly where you are now.
AI DS Course Snapshot
Data Science and Artificial Intelligence Course
AI DS Course
₹50,000 / full program
No-cost EMI options available
- + Live instructor-led training
- + 4 real-world ML capstone projects
- + Python, Scikit-learn & Deep Learning tool access
- + Resume, mock interviews & job assistance
- + Certificate of completion
Frequently asked questions
At Technogeeks X AI data science course syllabus covers Python programming, statistical modeling, data wrangling (Pandas, NumPy, SQL), machine learning algorithms (regression, classification, clustering), deep learning, NLP, and modern Generative AI systems.
Data science mainly focuses on things like data processing, exploratory analysis, and predictive modeling, while artificial intelligence focuses on building intelligent algorithms, neural networks, and automated systems. In this AI and Data Scientist course in pune learn both skill sets.
Yes. These data science classes in pune are good for both beginner and working professional with Phase 01 starting from fundamental Python syntax and basic statistics, making it beginner-friendly for fresh graduates and transitioning professionals.
After completing Technogeeks X AI data science training in pune you qualify for roles such as Data Scientist, Machine Learning Engineer, AI Analyst, Business Intelligence Consultant, and AI/ML Associate.