Learn Machine Learning the practical way.
Machine Learning and Deep Learning from zero to deployed. Animated algorithms, hands-on Colab checkpoints, and a learning path picked by your dataset: image, text, video, or tabular.
Start with what you actually have
Most ML guides teach algorithms first. We start from your data. Pick your dataset type, and we map the exact course path.
Image
Classification, detection, segmentation. OpenCV to CNN to deploy.
Text and NLP
Sentiment, classification, Malay and mixed-language, fine-tune BERT.
Video and time-series
Frames, optical flow, action recognition, LSTM and GRU sensors.
Tabular
Feature engineering, XGBoost and LightGBM, SHAP explainability.
34 courses, from zero to deployed
Foundation for everyone, data tracks by dataset, then the deployment and production gap universities skip, capped by a capstone project. Plus 19 standalone algorithm courses you can take one at a time.
Python for ML
Colab and Jupyter from zero.
FreeData Understanding and Preprocessing
Clean, visualize, statistics, and split real data.
from RM5.90Machine Learning Foundations
Learning, loss, and gradient descent, the intuition.
from RM5.90Model Evaluation and Tuning
Confusion matrix, F1, tuning, cross validation.
from RM5.90Deep Learning Fundamentals
Neuron to network, backprop animated.
from RM5.90Computer Vision I
OpenCV: thresholding, edges, morphology.
from RM5.90Computer Vision II (DL)
CNN internals, transfer learning, YOLO and R-CNN.
from RM5.90Text and NLP
TF-IDF, embeddings, fine-tune BERT.
from RM5.90Video and Time-Series
Optical flow, action recognition, LSTM.
from RM5.90Tabular
XGBoost and LightGBM, SHAP explainability.
from RM5.90Reinforcement Learning
Reward, Markov decision processes, Q-learning.
from RM5.90Big Data Engineering
MapReduce, Spark, and data at scale.
from RM5.90Model Deployment
FastAPI, connect to a web app, Docker basics.
from RM5.90Optimization for Production
Quantization, pruning, ONNX, TF-Lite.
from RM5.9030 projects to practice
Reading is not enough. Pick a small project and build it end to end. Each one maps to an algorithm you learn here and uses a beginner friendly dataset.
Pay for access, not a subscription
No recurring billing. Buy a pass, get full access for the period. We email you before it expires.
- Python for ML, full
- Preview all courses
- Community access
- All 34 courses
- Hands-on checkpoints
- Certificates
- Everything in Monthly
- New monthly courses included
- Priority checkpoint review
- Everything in Semester
- Bonus resources
- Best value per month
Project Mentorship, private 1-on-1
A personal review of your ML project, FYP or work project. From a quick FYP Review for students to a full 2-hour deep dive. Limited slots.
Common questions
Everything you need to know before you start learning Machine Learning with EpochLab.
Do I need a Computer Science background?
Do I need to know Python first?
Is this only for final-year project (FYP) students?
What kind of data can I learn to work with?
How much does it cost?
Are the certificates accredited?
What language are the lessons in?
We coach. We do not build your project for you.
Our helper tools guide you to build your own work, they never generate your deliverable. Certificates prove practical effort and skill, and are honestly not accredited. That is the integrity line, and we hold it.