0517 - Hands-on Machine Learning
Course Description
Overview
Unlock your full potential with real-world machine learning projects
Take your machine learning journey to the next level with this hands-on, eight-week course designed to give you real-world experience in applying your skills. As the final step in our comprehensive machine learning program, this course immerses you in a collaborative project where you’ll tackle meaningful, real-world challenges using the latest machine learning techniques.
Through this course, you’ll:
- Gain extensive experience working with Python and powerful machine learning libraries like scikit-learn, Pandas, and Matplotlib.
- Apply Agile methodology to manage your project, giving you critical skills to thrive in fast-paced tech environments.
Each week, you’ll stay actively engaged with hands-on tasks, from data preparation and model selection to hyperparameter tuning and performance evaluation. You’ll work on supervised learning and dive into deep learning and algorithm optimization—all while sharpening your collaboration skills in a team-based setting.
By the end of the course, you’ll have completed a comprehensive machine learning project that showcases your ability to solve real-world problems, optimize models, and work effectively within a team. This capstone project will not only demonstrate your technical expertise but also prove your readiness to tackle the challenges of today’s evolving data science and machine learning industries.
Who Should Enrol
- Tailored for professionals or learners looking to solidify their machine learning skills by applying them to real-world challenges, particularly in collaborative environments.
- Designed for intermediate learners who have completed the Supervised Machine Learning course.
What you Will Learn
Learning outcomes:
- Demonstrate the ability to clean, preprocess, and explore complex datasets to identify patterns, trends, and potential issues.
- Apply machine learning techniques to real-world problems.
- Implement a complete machine learning project using Python and relevant libraries, from inception to presentation.
- Critically evaluate machine learning models and their performance.
- Collaborate effectively in teams using Agile project management principles.
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Module 1: Introduction and Project Planning (Ideation) |
Get introduced to Agile project management, form project groups, and brainstorm project ideas. |
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Module 2: Project Proposal and Data Preparation |
Develop a project proposal by selecting a project idea, defining requirements, setting up a project management tool, preparing data, and creating initial visualizations. |
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Module 3: Model Selection and Baseline Implementation |
Explore model selection by reviewing supervised and unsupervised (if appllicable) learning techniques and implementing a baseline model with initial justification. |
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Module 4: Model Tuning and Optimization |
Optimize the model through hyperparameter tuning, evaluation with cross-validation, and regularization, while considering ethical implications and model bias. |
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Module 5: Project Development and Testing |
Finalize the model and project results, and prepare the final report and presentation. |
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Module 6: Project Presentation |
Present the completed project, reflect on lessons learned, and discuss future applications and learning opportunities. |
Applies Towards the Following Certificates
- Machine Learning Project Specialist : Mandatory
- Supervised Machine Learning and Hands On Machine Learning Bundle : Bundle Purchase