In today’s data-intensive world, traditional data science is evolving. Businesses, research institutions, and governments demand not just insights, but predictive power, intelligent automation, and innovative solutions. Generative AI is supercharging the field of data science—and this course is your gateway to mastering this powerful synergy.
“Data Science with Generative AI” is a pioneering program designed for aspiring data scientists, current analysts, engineers, and strategic thinkers looking to build and deploy sophisticated AI-driven solutions. By fusing core data science principles—statistics, programming, machine learning—with cutting-edge GenAI applications, this course empowers learners to move from foundational analysis to AI-assisted model development, automated insight discovery, and intelligent system creation.
You will explore the full data science lifecycle—from complex data acquisition and preparation to advanced modeling and deployment, all enhanced by AI. You will gain hands-on experience with essential tools like Python, SQL, Scikit-learn, TensorFlow/PyTorch (introductory), cloud platforms, ChatGPT, and more, understanding how to leverage GenAI to accelerate research, generate synthetic data, optimize algorithms, and interpret complex models at scale.
Whether you’re transitioning into data science or a seasoned professional seeking to integrate AI, this course will equip you with the hybrid skills in high demand across innovation-led industries such as tech, finance, healthcare, R&D, and autonomous systems.
🎓 Outcome: Graduate with an industry-ready portfolio showcasing end-to-end data science projects and the ability to leverage GenAI as a powerful collaborator in your data science endeavors.
✨ Why Choose EdTech Informative?
EdTech Informative is not just a platform — it’s a career catalyst. In a world where technology evolves faster than ever, we stay ahead of the curve to bring you industry-relevant, AI-powered, and practically driven learning experiences. Here’s why thousands of learners and professionals trust us:
✅ 1. Future-Ready Curriculum
Our courses are designed in collaboration with industry leaders, focusing on emerging trends like Generative AI, MLOps, Responsible AI, and AI-augmented data science. We don’t just teach skills — we teach what’s next.
👩🏫 2. Learn from Real Practitioners
Our instructors are seasoned data scientists, AI researchers, and machine learning engineers who work in the field — not just teach it. You’ll learn real-world applications, not just textbook theory.
🧠 3. Hands-On Learning Approach
We focus on project-based, practical education. Every course includes capstone projects, industry case studies, and tools like ChatGPT, Python, major ML libraries, and cloud services — so you build a real portfolio.
🔄 4. AI-Powered Learning Tools
We integrate AI tutors, real-time code generation, and intelligent feedback systems to personalize your learning. It’s like having your own AI assistant for every lesson.
🛠️ 5. Job-Ready Outcomes
From resume help to mock interviews and job referrals, we don’t stop at training. We help you land the role, with support from our career success team and hiring network.
🌐 6. Learn Anytime, Anywhere
Our flexible, cloud-based learning platform is mobile-optimized and self-paced. Learn when you want, how you want — whether you’re working full-time or learning on the go.
🏅 7. Certification That Matters
Our certifications are recognized by top employers and showcase your readiness to work with cutting-edge tools in data science and AI.
At EdTech Informative, you’re not just learning — you’re evolving.
Transform how you model, predict, and innovate with AI-powered data science skills that employers want and the world needs.
🌟 Why Join This Program?
💼 Microsoft Advantage: Learn from the Best
Unlock elite training straight from Microsoft. Gain hands-on experience with Azure AI and Machine Learning services, validate your skills with an industry-recognized certification, and set yourself apart with credentials that hiring managers trust. This is your fast track to becoming a certified, job-ready professional.
🤖 Generative AI Edge: Stay Ahead of the Curve
Don’t just keep up—lead the AI revolution. Dive into exclusive live sessions on Generative AI, prompt engineering for complex tasks, and the latest advancements transforming data science. Learn how to harness cutting-edge tools like ChatGPT for code generation, hypothesis testing, and even synthetic data creation to amplify your data science capabilities and stay future-ready.
🛠️ Hands-on Learning: Built for Real-World Impact
This isn’t theory—it’s action. Learn live from top industry experts and apply your knowledge through practical exercises, case studies, and job-ready capstone projects. Walk away with a portfolio that proves your value from day one.
🎯 Placement Support: Your Career, Supercharged
Our commitment doesn’t end at the final module. Get 100% placement assistance through our dedicated recruitment network, with access to 250+ hiring partners. Thanks to our tailored career coaching and industry connections, we’re proud to have an 90% placement success rate. Your success is our mission.
Course Modules:
Module 1: Introduction to Data Science and AI
- The role and impact of a data scientist
- The Data Science lifecycle: From problem formulation to deployment (e.g., CRISP-DM)
- Overview of AI, Machine Learning, Deep Learning, and Generative AI
- Ethical considerations in AI and Data Science
- Use cases in various industries and AI-driven innovation
Module 2: Advanced Data Foundations & Engineering
- Advanced data types, structures, and storage (NoSQL, Data Lakes)
- Data acquisition (APIs, web scraping) and wrangling with Python (Pandas, NumPy)
- Data cleaning, preprocessing, and feature engineering techniques
- SQL for complex querying, data manipulation, and database management
Module 3: Statistical Modeling & Rigorous EDA
- Advanced descriptive and inferential statistics for data science
- Probability distributions, sampling, and hypothesis testing
- Regression analysis (linear, logistic) and ANOVA
- Advanced Exploratory Data Analysis (EDA) with Python (Matplotlib, Seaborn, Plotly)
- Automating and augmenting EDA with GenAI prompts for deeper insights
Module 4: Python for Data Science & GenAI Integration
- Mastering Python for data science: Pandas, NumPy, SciPy, Matplotlib, Seaborn
- Object-Oriented Programming (OOP) concepts for scalable code
- Using GenAI (e.g., ChatGPT, GitHub Copilot) for efficient code generation, debugging, and documentation
- Developing custom Python scripts for data processing and automation, assisted by AI
Module 5: Machine Learning – From Theory to Application
- Core ML concepts: Supervised (classification, regression), Unsupervised (clustering, dimensionality reduction) learning
- Key algorithms: Decision Trees, Random Forests, SVM, K-Means, PCA
- Model training, tuning (hyperparameter optimization), and evaluation metrics
- Introduction to Scikit-learn library for ML model implementation
- AI-assisted model selection and initial parameter tuning using GenAI
Module 6: Generative AI for Data Scientists
- Deep dive into Generative AI: LLMs (e.g., GPT series), diffusion models, GANs, and Agents
- Advanced prompt engineering for data science: synthetic data generation, feature creation, anomaly detection insights
- Leveraging GenAI for natural language to SQL/Python, complex query generation
- GenAI for automated report writing, insight summarization, and code explanation
- Exploring multimodal GenAI: processing text, image, and structured data in workflows
Module 7: Advanced Machine Learning & AI-Powered Optimization
- Introduction to Deep Learning: Neural Networks, TensorFlow/Keras or PyTorch basics
- Ensemble methods, gradient boosting (XGBoost, LightGBM)
- Model interpretability and explainable AI (XAI) techniques (e.g., SHAP, LIME)
- AutoML tools and GenAI for accelerating model development, feature selection, and hyperparameter tuning
- Time series analysis and forecasting with classical and ML methods, augmented by GenAI
Module 8: Capstone Project: End-to-End Data Science with GenAI
- Select a complex real-world problem (e.g., predictive maintenance, fraud detection, customer churn)
- Execute a full data science project: data acquisition, preprocessing, modeling, evaluation, and interpretation
- Integrate GenAI tools strategically for tasks like data augmentation, code optimization, insight generation, and creating compelling narratives/presentations
- Develop a comprehensive, portfolio-ready project demonstrating mastery of data science principles and GenAI application
- Peer review, industry expert feedback, and presentation of findings
