Advanced Certificate in Applied Data Science and Analytics (I) Module 4: Machine Learning Using Python
About This Course
Module 4 explores the development of essential machine learning algorithms to address prediction and forecasting challenges encountered in diverse business contexts. Building on the foundation laid in Module 1 with linear regression theory, this module introduces participants to key concepts including Logistic Regression, Decision Tree, Ensemble Methods (Random Forest and Gradient Boosting Machines) and Basics of Time Series Forecasting.
Participants will apply these algorithms using Python to tackle a range of prediction and forecasting tasks relevant to business scenarios. Practical exercises with provided datasets will reinforce their understanding and proficiency in applying these methods effectively.
What You'll Learn
• Learn few commonly used machine learning techniques that are essential for a Data Scientist journey
• Be familiar with the data types that can be used for different algorithms
• Appreciate the variety of applications of these machine learning techniques for analysing data and perform prediction and forecasting using python
• Learn to interpret software output to assess the quality of the models and methods to improve the models for better accuracy in prediction and forecasting
Entry Requirements
This programme is structured to provide a comprehensive learning experience. Participants are required to complete the modules in the designated sequence to ensure a solid understanding of each topic before moving on to the next.