This program covers a recap of basics in Python programming plus concepts and
implementations of Machine Learning (ML) including regression, classification and clustering
using Python and libraries like Keras and SK learn. This includes ML algorithms like linear and
logistic regression, KNN, decision trees, support vector machines, K-means, neural networks
along with their applications. Further it focuses on recent research trends in ML and an
introduction to industry implementations of ML algorithms using cloud-based tools and
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
linear and logistic
Discussion on SK learn and Keras for ML Including model training and evaluation
KNN, DT, SVM, Ensemble Systems
8.0 Neural Networks
9.0 Machine Learning in the Cloud (MLaaS)
10.2 Research Opportunities
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
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.
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
: Informatics Institute of Technology Limited
: 0036 1000 3876
: Sampath Bank
: Wellawatte Super
: Invoice No or NIC Number
For further details, please contact
IIT Professional Development Unit
0770 566 577 | email@example.com