About this Event
Course Overview
Machine learning is a topic which is leading the trend in the transformation of organisations from digitisation to data-driven. This course aims to expose the learner to the code underpinnings of constructing and assessing a subset of the machine learning tasks, namely the classification, time series and clustering/feature extraction tasks. The objective is to target commonly encountered tasks in the space of financial data analysis. Participants will be able to gain familiarity in such tasks and have a deeper understanding of tackling them.
Course Duration
2 days (16 hours)
Course Fee
$866.70/- (GST Inclusive)
Medium of Instruction: English
Mode:
Webinar
Course Outline
Day 1:
Module 1:
To enable learners to have an overall understanding of the landscape of Data Mining and Machine Learning.
Introduction: Machine Learning and Data Mining
Supervised and Unsupervised learning techniques
Module 2:
To give the participants the very first steps towards forming hypothesis and doing predictive analytics, learning some of the classification techniques in supervised learning.
Machine Learning and Classification
Classification: Logistic Regression, Decision Trees, Random Forest, XGBoost
Module 3:
It aims to equip participants with the basics of how supervised machine learning models work and how evaluation and optimization can be carried out.
Evaluation and Metrics
Understanding and comparing model results
Feature importance
Day 2:
Day 2 will continue the journey for the learners in machine learning with focus on Neural Networks and Unsupervised learning techniques.
Module 4:
This module work with exploring time-based data, here participants will learn about how to assess and play with past data to explain future movements.
ARIMA model – seasonality
Module 5:
To equip learners in understanding some of the Unsupervised learning techniques which is required for machine learning.
Clustering and Segmentation
Principal Component Analysis
Feature Reduction
AB Testing
Module 6:
To further equip learners with knowledge on neural networks, this is a flexible method for which new machine learning fields are being pioneer.
Introduction to neural networks
Working with a neural network
Learning Outcome
Construct analytics models/results as part of solutions to address business problems
Evaluate the performance of analytics models
Analyse the results or outputs of analytics models
Evaluate the importance of features which are used
Understand how to reduce features
Mode of Assessment
Written and Practical
System Requirements
Windows OS or MAC OS installed with anaconda
Page Link: Click here to know more and register
Website: Click here
Contact Number: +65 9106 3805
Name: Avanta Global
Email ID: [email protected]
Event Venue & Nearby Stays
BS Bendemeer Centre, 20 Bendemeer Road, Singapore, Singapore
SGD 0.00