This program blends analytics, machine learning, deep learning, and practical AI so every week ends with something real—dashboards that reveal patterns, models that predict outcomes, and apps that feel smarter with each iteration. The goal is simple: build confidence, build projects, and build a career in Kerala’s fast-moving tech ecosystem.
This program is designed to reflect how modern AI and data teams actually work. Instead of focusing on theory alone, you’ll move through short demos, guided notebooks, and weekly deliverables that grow naturally from data cleaning to full model deployment.
Every concept—from handling messy datasets to evaluating algorithms—is reinforced through hands-on labs and real projects. Mentors keep feedback practical, focusing on metrics, overfitting, feature engineering, and storytelling, so you always know what to improve and why.
The course runs in modern labs with structured placement support to ensure your portfolio is interview-ready and highlights your best work.
Available in Trivandrum, Kochi (Aluva), and Thrissur
Collect, clean, and model data. Build dashboards that answer real questions using DAX-style measures, visual grammar, and presentation techniques for non-technical teams.
Write clean, reusable analysis code with pandas, NumPy, and matplotlib/seaborn. Keep your projects organized with structured notebooks and functions.
Understand distributions, sampling, hypothesis testing, and confidence intervals to make data-backed decisions that hold up under scrutiny.
Work through the full model lifecycle—feature engineering, validation, cross-validation, and error analysis. Apply regression, classification, ensembles, and clustering effectively.
Use embeddings and APIs to build intelligent search, classification, and assistive features. Connect models to real applications and workflows.
Understand how layers, activations, and optimizers work. Build image and text models using TensorFlow or PyTorch and apply transfer learning for efficiency.
Prototype AI assistants, content tools, and chat systems using prompt design, retrieval-augmented generation (RAG), and responsible AI practices.
Query, join, and aggregate data confidently. Learn how to move from ad-hoc analysis to building repeatable ETL pipelines for analytics and AI workflows.
Turn analysis into narratives—define problems, highlight key insights, and link findings to real-world business decisions and KPIs.
Graduate ready to contribute as a Data Analyst, Business Analyst, ML Engineer (entry), AI Engineer (entry), or Junior Data Scientist. You’ll finish with a portfolio that demonstrates your ability to solve real problems using data, ML, and AI.
Mentor-led sessions in analytics, ML, and deep learning with weekday and weekend batches. Projects reflect real local business use cases.
Hands-on modeling, BI dashboards, and AI prototypes with strong emphasis on problem framing and storytelling for business impact.
Project-first learning approach focusing on models, visuals, and presentations. Includes dedicated placement assistance to turn your skills into offers.
Build your IT foundation from the ground up. Master networking, CCNA concepts, Linux, cloud, and cybersecurity with guided labs that simulate real-world troubleshooting. Ideal for students aiming for an IT or network engineering career.
Learn how to promote any brand online with SEO, Google Ads, social media, and content marketing. Work on live campaigns that teach you how to attract, engage, and convert real customers — perfect for freelancers and marketing beginners.
Build full-stack applications from scratch — HTML, CSS, JavaScript, React, Python, databases, and DevOps. Gain project management and agile skills to deliver software that’s efficient, scalable, and ready for real clients.
Talk to a counselor—choose a branch, map modules to goals, and set a date to start building models that matter.