Professional Certificate in Machine Learning
Requirements:
Knowledge in Python, Coding
Description:
Why Machine Learning?
In a data-driven era, machine learning is the driving force behind intelligent decision-making and problem-solving. Join us to explore the frontiers of artificial intelligence, where algorithms learn from data to uncover insights, predict outcomes, and revolutionize industries.
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, and 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 services.
Enroll Today and Engineer Intelligent Solutions!
Ready to unlock the potential of intelligent machines? Enroll now and let’s embark on a journey where you not only learn the intricacies of machine learning but also contribute to shaping the future of artificial intelligence
Course Details
Opting for a career as a machine learning engineer ensures a stable and promising future. Recently identified as the second most in-demand AI job, the pandemic has heightened the significance of artificial intelligence and machine learning fields. Choosing a machine learning profession offers a lucrative and enduring career, given the increasing prevalence of AI in industries like healthcare, education, marketing, retail and e-commerce, and financial services.
Course Outline
Python recap procedural and OOP.
Introduction to Machine Learning Ideas of regression, classification, clusterin.
Neural Networks and Deep NN.
Regression linear and logistic.
Discussion on SK learn and Keras for ML Including model training and evaluation
KNN, DT, SVM, Ensemble Systems.
Clusterning.
K-mean.
Neural Networks.
Machine Learning in the Cloud (MLaaS).
ML OPS.
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
How to Apply?
For further details, please contact
IIT Professional Development Unit
0770 566 577 | pdu@iit.ac.lk
Address : 57, Ramakrishna Road, Colombo 06, Sri Lanka.
Phone : 766760760
Email : info@iit.ac.lk
Website : https://www.iit.ac.lk
Available:
Informatics Institute of Technology
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Stream: Computer Science & IT
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Level: Professional Certifications