Machine Learning using Python Course in Singapore
The machine learning software enables the application to improve their ability to predict results over time. By analyzing historical data, machine learning algorithm can identify the pattern and use them to predict future consequences with greater accuracy.
Schedule
- Days: 2 Days
- Duration: 16 Hours
- Timings: 9:30 AM - 5:30 PM
- 10 Anson Road, 26-08A International Plaza, Singapore 079903
Why Choose Us
- Expert Local Trainers
- Hands-on Training by experts
- Certificate of Achievement
Who Should Attend This Machine learning with python Course
Machine learning with Python is ideal for those who want to become a data scientists. Participants should have a background in programming in Python before attending.
Business professionals
Analyst
Entrepreneur
Training Professionals
Student
Course Completion Requirements
Minimum 75% attendance is required in order to complete the course and receive the course completion certificate
Above 16 years old
High School Level English
Basic internet & computer operation skills
About the Course
These are the important outcomes that learners will get:
- Learn the basic concepts of scikit-learn
- Learn the implications of machine learning
- Learn when to apply unsupervised learning algorithms
- Implications of how several machine learning algorithms wor
- Learn how to perform supervised learning algorithms to business cases
- Understand how to program supervised learning algorithms using Python
- Learn how to test and authenticate machine learning models
- Learn important concepts of model evaluation and performance metrics
- Understand how to optimize machine learning models using various techniques
- Understand advanced machine learning algorithms
Begin your Machine Learning career with us
Data Analytics knowledge is compulsory, and recommended to join the basic Python course before joining this course.
What You’ll Learn
Machine Learning with Python is an advanced-level course that teaches you how to write algorithms and code in Python to perform complex analytics. You’ll learn to build, train, and evaluate a variety of machine learning models to make predictions and generate actionable insights.
Machine Learning using Python Course Outline
Module 1
The main objective of this module is to learn the basics of Data Preparation and understand the essentials of machine learning in terms of functional & non-functional processes.
- Restoring the essential techniques in python as an essential to machine learning
Module 2
The main goal of this module is to learn the fundamentals of machine learning with Sckikit-learn. Also, you can learn important libraries of machine learning in this module.
- Understand the machine learning flow and concepts
- Learn functions within scikit-learn
- Prologue to supervised and unsupervised machine learning
Module 3
The main objective of this module is to learn Unsupervised Machine Learning. It uses a very famous python library known as scikit-learn. Unsupervised learning is very important in different business cases today, right from client division to property analysis.
- Learn unsupervised ML algorithms
- Understand clustering (k-means, SOM)
- Executing clustering with real use cases
Module 4
The main objective of this module is to learn Supervised Machine Learning. Unde Supervised Machine Learning Supervised machine learning is one of the most popular techniques in machine learning today. This module will focus on some of the most famous algorithms in regression and classification and equip learners with an understanding of how the algorithms execute.
- Learn various supervised learning algorithms
- Learn feature engineering and feature sets
- Execute numerous Supervised ML algorithms with real use cases
Module 5
The main goal of this module is to learn machine learning models and data science lifecycle. Also, you will learn model selection, evaluation, and optimisation.
- Learn model selection and evaluation methods
- Learn how to optimize machine learning models
Frequently Asked Questions (FAQs)
Who should consider taking this course?
This advanced-level training is perfect for professionals like analytics managers, developers, business analysts, information architects, and graduates looking to build a career in machine learning.
What prerequisites are required?
How long is the course and what does it cover?
This is a two-day intensive course. You’ll begin with data preparation fundamentals, then dive into both supervised and unsupervised learning using Python’s Scikit-Learn library. You’ll also learn how to evaluate and validate your machine learning models
Are there any certification or attendance requirements?
Yes—participants must attend at least 75% of the sessions to receive the course completion certificate