Data Science & Machine Learning
From Python foundations to building and deploying ML models.
Overview
About this course
A structured, eight-phase pathway that takes you from zero programming knowledge to building and deploying machine learning models. Each phase builds progressively, with clear topics, tools, and certification guidance aligned to what the industry actually expects.
Who it's for: Aspiring data scientists and analysts, no prior programming required.
What you'll learn
Skills you'll walk away with
- Program confidently in Python for data work
- Apply the maths and statistics behind machine learning
- Wrangle, analyse, and visualise real-world datasets
- Query data with SQL and relational databases
- Train, tune, and evaluate ML models with scikit-learn
- Build and present an end-to-end portfolio project
Curriculum
Your step-by-step learning path
- Python syntax, variables, data types, and operators
- Control flow: conditionals, loops, and iteration
- Functions, scope, lambda expressions, and decorators
- Object-oriented programming: classes, inheritance, polymorphism
- File handling, exceptions, and working with modules
- Virtual environments and package management with pip
Python 3.xVS Code / PyCharmJupyter Notebookpip / conda
Tools & technologies
What you'll work with
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