Course Details

Courses Descriptions

📝 Long Description:

Launch Your Career in Data Science, ML, and Generative AI — with Solid Coding Skills!

This 5-month comprehensive course is designed for learners who want to become job-ready Data Scientists, AI Engineers, or ML Developers with strong coding and analytical skills.

You’ll start with a foundation in Python programming and Data Structures & Algorithms (DSA), preparing you for real-world problem solving and tech interviews. Then, you’ll dive deep into core data science concepts, machine learning, and model building. You’ll also explore the fast-evolving world of Generative AI (GenAI)—working with tools like ChatGPT, LangChain, Hugging Face, and building AI-powered applications.

The course is packed with hands-on labs, mini-projects, and capstone challenges to solidify your skills. Whether you’re switching careers or upskilling, this course is your gateway to top-tier data roles.

✅ Strong Python & DSA Foundation
✅ Practical ML & GenAI Implementation
✅ Projects with Real-World Datasets
✅ Pre-recorded + Self-paced Learning
✅ Portfolio & Resume Building Support
✅ Interview Prep and Mock Interviews (Optional Add-on)

📦 Course Modules:

🔹 Month 1: Python Programming & Core DSA

• Python basics to advanced

• Lists, Dictionaries, Tuples, Sets

• Functions, Loops, Conditions

• OOP in Python

• Data Structures: Arrays, Linked Lists, Stacks, Queues

• Sorting & Searching Algorithms

• Time and Space Complexity

• Leetcode/InterviewBit Practice

🔹 Month 2: Mathematics & Statistics for Data Science

• Linear Algebra essentials

• Probability & Combinatorics

• Descriptive & Inferential Statistics

• Hypothesis Testing

• Z-Test, T-Test, ANOVA

• Correlation & Regression

🔹 Month 3: Data Analysis & Visualization

• Numpy, Pandas for data manipulation

• Matplotlib, Seaborn, Plotly for visualization

• EDA on real-world datasets

• Data Cleaning, Feature Engineering

• Handling missing values, outliers

• Data Wrangling Projects

🔹 Month 4: Machine Learning + Projects

• Supervised vs. Unsupervised Learning

• Linear & Logistic Regression

• Decision Trees, Random Forest

• KNN, K-Means, SVM, Naive Bayes

• Model Evaluation (Accuracy, Precision, Recall, F1, ROC)

• Model Tuning (GridSearch, Cross Validation)

• Real-world ML projects (fraud detection, sales prediction, etc.)

🔹 Month 5: Generative AI (GenAI) & Capstone

• Introduction to GenAI & Prompt Engineering

• ChatGPT & OpenAI API integration

• LangChain for custom AI applications

• Hugging Face Transformers

• AutoML tools (Google AutoML, PyCaret)

• Building GenAI-powered apps (chatbots, content generation)

• Final Capstone Project: End-to-end DS/ML/GenAI solution

🎯 Tools & Platforms Covered:

• Python, Jupyter Notebook, VS Code

• Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn

• OpenAI, LangChain, Hugging Face

• GitHub, Colab, AutoML, SQL (Basics)

🎓 Outcome:

• Be job-ready for roles like Data Scientist, ML Engineer, GenAI Developer, AI Product Analyst, or Data Analyst

• Strong portfolio with 5+ projects

• Certification, resume prep, and mock interviews (available with career track)