Machine Learning (ML) CourseLive online across India · Tamil & English · Classroom in Rasipuram, Tamil Nadu
Live machine learning course — Python, scikit-learn, model building and deployment — online for learners across India, or in our Rasipuram classroom (Tamil Nadu). Placement support.
Course overview
Machine Learning with Artificial Intelligence: From Basics to Advanced Applications
Course Description:
Unlock the power of Machine Learning and AI with GeekBase Technology’s industry-focused training program. This course is designed to take learners from foundational concepts to advanced AI applications. Through hands-on projects, real-world datasets, and expert guidance, learners will gain the skills needed to build intelligent systems and launch careers in AI/ML.
Key Highlights:
Target Audience:
Students interested in AI/ML careers.
Developers looking to transition into Data Science / AI-ML.
Professionals aiming to upskill in ML technologies.
Prerequisites:
Basic Python programming experience is required for this course. However, basic computer literacy and familiarity with using a computer are recommended.
Mentor Support:
Learners will have access to an experienced instructor who will provide support through one on one meeting, live Q&A sessions, and email to answer questions and provide guidance throughout the course.
Learn online from anywhere in India — or in our classroom
🌐 Live online — pan India
Join live, trainer-led Machine Learning (ML) classes from any city or town in India. Ask questions in class, get your code reviewed and practise on GoCode between sessions.
🏫 Classroom — Rasipuram
Prefer learning in person? Our centre in Rasipuram (Namakkal district) is a short trip from Salem, Namakkal, Erode and Tiruchengode.
Curriculum
12 modulesModule 1: Introduction to AI & Machine Learning
- What is AI, ML, Deep Learning.
- Applications of AI in real world.
- Types of Machine Learning (Supervised, Unsupervised, Reinforcement).
- ML workflow.
Module 2: Python for Machine Learning & Data Science
- Python basics (variables, loops, functions).
- Lists, dictionaries, tuples
- NumPy basics.
- Pandas (DataFrames, operations).
- Data visualization (Matplotlib, Seaborn).
- Data preprocessing.
Module 3: Statistics & Mathematics for ML
- Mean, Median, Mode.
- Probability basics.
- Correlation & covariance.
- Linear algebra basics.
Module 4: Data Preprocessing
- Handling missing values.
- Encoding categorical data.
- Feature scaling.
- Train-test split.
- Outlier Detection :Z-score method,Feature Selection.
- Feature Selection :Filter methods(correlation), Wrapper methods, Embedded methods.
Module 5: Supervised Learning – Regression
- Linear Regression.
- Multiple Regression.
- Model evaluation (MSE, RMSE, R²).
Module 6: Supervised Learning – Classification
- Logistic Regression.
- K-Nearest Neighbors (KNN).
- Decision Trees.
- Random Forest.
- Boosting Algorithms -AdaBoost (basic intro)
- XGBoost (Industry standard)
Module 7: Unsupervised Learning
- Clustering (K-Means).
- Hierarchical clustering.
- Dimensionality reduction (PCA basics).
Module 8: Model Evaluation & Optimization
- Confusion matrix.
- Accuracy, Precision, Recall, F1-score.
- Cross-validation.
- Hyperparameter tuning.
Module 9: Introduction to Deep Learning
- Neural Networks basics.
- Activation functions.
- TensorFlow / Keras basics.
- Simple ANN model.
Module 10: Natural Language Processing (NLP)
- Text preprocessing.
- Tokenization.
- Bag of Words / TF-IDF.
- Basic sentiment analysis.
- Introduction to Modern AI
- Introduction to LLMs (Large Language Models)
- Basics of Transformers architecture
- Real-world applications (ChatGPT, Bard, etc.)
- API usage overview (optional demo)
Module 11: Computer Vision Basics
- Image processing basics.
- OpenCV introduction.
- Image classification concepts.
Module 12: Deployment & Final Project
- Model deployment basics (Flask / Streamlit).
- Building end-to-end ML project.
- Real-world project - House price prediction.
- Real-world project - Spam detection system.
- Real-world project - Number plate detection.
- Real-world project - Face recognition system.
- Real-world project - Chatbot creation.
- Real-world project - FAQ bot using LLM APIs.
Certification
Course Certification:
Upon successful completion of the course, there will be cumulative test conducted and students who scored above 60% marks will receive a certificate of completion from GeekBase Technology, which can be used to showcase their newly acquired Machine-Learning - AI skills.
Note: Test will be a MCQ pattern and maximum two attempts allowed.
Why certified Machine-Learning with AI ?
Frequently asked questions
Can I join the Machine Learning (ML) course from outside Tamil Nadu?
Yes. The live online batch is open to learners anywhere in India — Chennai, Bengaluru, Hyderabad, Pune, Kochi or a small town. You attend the same live classes, with the same trainers and curriculum, as the classroom batch. Classes are taught in Tamil, English.
Where is the classroom for the Machine Learning (ML) course?
Our classroom centre is on Bharathidhasan Street, Rasipuram (Namakkal district) — between Salem and Namakkal, and within reach of Erode and Tiruchengode.
What is the fee and duration of the Machine Learning (ML) course?
The course runs for 15 Weeks and the fee is ₹32,000 (regular price ₹40,000). EMI options are available — message us on WhatsApp for the current batch dates and offers.
Do I get a certificate and placement support?
Yes. You receive a course completion certificate, and placement support includes resume reviews, mock interviews and practice on GoCode, our coding and interview-prep platform.
