Data Science Machine Learning Course
Master the full data science and machine learning stack, from Python fundamentals and statistical theory to deep learning and production deployment. This course covers every stage of the ML workflow with hands-on projects and real datasets. Build the skills employers are actively hiring for and finish with a portfolio-ready capstone project.
flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
You will build a strong foundation in Python, linear algebra, probability, and calculus as they apply directly to machine learning. From there, you will master supervised and unsupervised learning algorithms, including regression, classification, clustering, and dimensionality reduction. You will design and train neural networks, including CNNs and LSTMs, using modern deep learning frameworks. The course also covers model selection, hyperparameter tuning, and rigorous validation strategies. You will learn to deploy models as REST APIs, monitor them in production, and manage the full ML system lifecycle. Supplementary modules on NLP, time series forecasting, responsible AI, and big data tools round out your skill set.
Elevify advantages
Develop skills
- Machine Learning Model Building: Train, tune, and evaluate regression and classification models on real datasets.
- Deep Learning Pipeline Design: Build and regularise neural networks for structured data and image recognition tasks.
- ML System Deployment: Wrap trained models in REST APIs and package them for production environments using Docker.
- Data Wrangling and Feature Engineering: Clean raw datasets and engineer high-impact features using pandas and Python.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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