AI & Machine Learning Training for Beginners

Kickstart your AI journey with DigiDARA’s 3-Month Beginner-Friendly AI & Machine Learning Training Program in Tiruchirappalli. Designed for students, professionals, and educators, this course covers Python, SQL, Data Structures, NLP, Computer Vision, Deep Learning, and MLOps using only open-source tools.

📅 Schedule: 5 Days a Week ⏰ 2–3 Hours per Day 🎓 Certification Included

Why Choose Our Data Science Course?

Hands-on Learning

Build real-world projects with AI and Machine Learning

Industry Certification

Get certified and build a portfolio-ready resume

Beginner Friendly

No prior coding experience required - start from basics

Career Support

Job-ready skills for Data Analyst and Data Scientist roles

Course Curriculum (Weekly Breakdown)

1

Weeks 1–2: Python Programming + Data Structures & Algorithms

Learn Python fundamentals—syntax, loops, functions, and object-oriented programming.

2

Week 3: SQL & Data Analysis with Pandas

Understand relational databases and write SQL queries for data extraction and aggregation. Use Pandas and NumPy for cleaning, transforming, and analyzing structured datasets, preparing them for machine learning models.

3

Week 4: Machine Learning with Scikit-learn

Dive into supervised and unsupervised learning. Build models like linear regression, decision trees, and clustering using Scikit-learn. Evaluate performance with metrics such as accuracy, precision, recall, and F1-score.

4

Week 5: Deep Learning Foundations (Neural Networks, CNNs, RNNs)

Learn the fundamentals of neural networks, activation functions, forward/backpropagation, and optimization. Understand CNNs for image data and RNNs for sequence data. Train your first deep learning models using TensorFlow and PyTorch.

5

Week 6: Computer Vision with OpenCV & CNNs

Explore the basics of computer vision. Work with OpenCV for image processing and implement CNN architectures for image classification, object detection, and recognition tasks.

6

Week 7: Natural Language Processing (spaCy, BERT, GPT)

Learn NLP techniques such as tokenization, lemmatization, and vectorization. Implement text classification and sentiment analysis. Use advanced Transformer models like BERT and GPT for state-of-the-art language understanding.

7

Week 8: MLOps & Model Deployment (Docker, MLflow)

Understand MLOps best practices for managing the ML lifecycle. Use Docker for containerization, FastAPI for deployment, and MLflow for tracking experiments, model versioning, and monitoring deployed models.

8

Weeks 9–12: Capstone Projects & Presentations

Apply everything you’ve learned to real-world domain projects in Finance, Healthcare, Education, and Retail. Build end-to-end ML/DL solutions—from data collection and preprocessing to modeling and deployment. Present your projects in Week 12 as portfolio-ready case studies.

Career Outcomes & Certification

Upon completion, you'll receive:

  • 1. Course Completion Certificate
  • 2. Build and deploy complete ML & DL models
  • 3. Apply MLOps practices to deploy & monitor models
  • 4. Collaborate with Git & GitHub for version control
  • 5. Develop an AI portfolio with production-ready projects
  • 6. Aligned to entry-level roles:
    • I. Machine Learning Engineer (Junior)
    • II. Deep Learning Assistant
    • III. Junior NLP Engineer
    • IV. AI Assistant

Capstone Project

Choose a domain like Retail, Healthcare, HR, Finance, or Education and deliver a full project:

  • 1. Finance: Stock price prediction, credit risk classification
  • 2. Healthcare: Disease detection from X-rays, risk modeling
  • 3. Education: Student performance prediction, resource recommendation
  • 4. Retail: Sales forecasting, product recommendation systems

Ready to Start Your AI and Machine Learning Journey?

Join thousands of students who have transformed their careers with our comprehensive training program.

Course Investment

Contact us for current pricing and payment plans

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Frequently Asked Questions

Who should attend this AI Leadership Program?

Business leaders, executives, and decision-makers aiming to lead AI adoption in their organizations.

What will I learn?

Generative AI, Agentic AI, governance frameworks, ROI analysis, vendor strategies, and future workforce readiness.

What is the duration of the program?

It’s a 6-week program with weekly executive sessions + a capstone project.

What will I achieve by the end?

A board-ready AI roadmap, cost models, and a working agent prototype aligned to your business.

What industries does this program cover?

Healthcare, finance, manufacturing, HR, operations, and education.

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