Data Science & Machine Learning with Python
A data science track covering numerical computing, exploratory data analysis, machine learning algorithms, and model deployment.
Duration
10 Weeks
Delivery Format
Project-Based Learning
Prerequisites
Developers, analysts, and STEM graduates aiming for data science & ML roles.
Curriculum Overview
This course is hands-on: most of the time goes into building working systems rather than lectures.
Core Competencies & Modules
Module 1: Numerical Computing with NumPy & Data Manipulation with Pandas
Lecture, worked example and an assessed coding assignment.
Module 2: Exploratory Data Analysis (EDA) & Data Visualization (Matplotlib, Seaborn)
Lecture, worked example and an assessed coding assignment.
Module 3: Supervised & Unsupervised Machine Learning with Scikit-learn
Lecture, worked example and an assessed coding assignment.
Module 4: Feature Engineering, Model Optimization & Evaluation Metrics
Lecture, worked example and an assessed coding assignment.
Module 5: Deploying ML Models via Web APIs & Real-world Industry Datasets
Lecture, worked example and an assessed coding assignment.
Certificate
Participants who complete all module assessments will receive a Radiece Program Completion Certificate.
Registration Status
Open for Enquiry
No batch scheduled yet. Batches open once enough interest is registered