infomatics institute of technology
infomatics institute of technology

Next Intake

December 2023
Intakes

Feb/Aug

infomatics institute of technology

Duration

2 ½ Months

(Part Time)

Saturdays 9.00 am to 1.00 pm

infomatics institute of technology

Entry Requirements

Knowledge in Python, Coding

Apply Now

Course Outline

1.0 Python recap
1.1 procedural and OOP
2.0 Introduction to Machine Learning (Pasan)
2.1 Ideas of regression, classification, clustering, Neural Networks and Deep NN
3.0/4.0 Regression
linear and logistic
Discussion on SK learn and Keras for ML Including model training and evaluation
5.0/6.0 Classification
KNN, DT, SVM, Ensemble Systems
7.0 Clustering
5.1 K-means

8.0 Neural Networks
9.0 Machine Learning in the Cloud (MLaaS)
10.1ML OPS
10.2 Research Opportunities

Learning Outcomes

1. Understanding and ability to apply the fundamental programming elements on Python and
its OOP concepts.
2. Understanding the types of machine learning algorithms in high level.
3. In-depth understanding of concepts and ability to apply supervised and unsupervised
machine learning techniques including Regression, Classification and Clustering for real-life
problems.
4. In-depth understanding of concepts and ability to apply Neural Network related machine
learning techniques like CNN, RNN and LSTM for real-life problems.
5. Ability to design, develop and deploy machine learning workflows in cloud based
environments like AWS, Azure, GCP.
6. Understanding of scientific research opportunities in the area of machine learning.

To Whom?

Those interested in learning ML and working in research and development in data-driven firms, as well as Research Students

Method Of Delivery

  • Option 1: Lab Demonstrations Face to Face
  • Option 2: Online/Distance classes through a digital learning platform

Course Fee & Payment Terms

  • Account Name
  • : Informatics Institute of Technology Limited
  • Account Number
  • : 0036 1000 3876
  • Bank
  • : Sampath Bank
  • Branch
  • : Wellawatte Super
  • Bank Code
  • : 7278
  • Branch Code
  • : 36
  • Your Reference
  • : Invoice No or NIC Number

For further details, please contact

IIT Professional Development Unit
0770 566 577 | pdu@iit.ac.lk

Apply Now