Overview

Certificate in Artificial Intelligence and Machine Learning

Artificial Intelligence

In order to build a variety of useful AI applications, students will have the chance to work with industry-required programming languages like Python and cutting-edge Machine Learning.

The course material also covers theoretical ideas related to data visualization, recommender systems, natural language processing, computer vision, and reinforcement learning.

Course details :

•         Introduction to Artificial Intelligence Development

•         Applied Mathematics for Artificial Intelligence Systems

•         Studies in Artificial Intelligence

•         Visualization and data storytelling

•         Artificial Intelligence Algorithms

•         Applied Machine Learning and Advanced Artificial Intelligence Systems

Machine Learning

Through the utilization of contemporary developments in computation and machine learning, this course seeks to introduce students to the quantitative analysis of data. You will go through important subjects like the difficulties of utilizing statistical approaches to analyze massive data and how machine learning and data science may help with knowledge creation and decision-making. Additionally, you will study quantitative approaches to text analysis, such as data mining from websites and social media.

Students will discuss the primary analytical techniques used in this area and practise applying them using real datasets while working with top teachers. You can gain experience and confidence using the techniques covered in the course in many contexts as a consequence of the training.

Course details : (Basics only)

•         Deep Learning

•         AI and ML

•         Data Science

•         Python

•         Statistics

Entry Requirement :

There are no formal entry requirements for this qualification, however A levels or equivalent preferably in physics / maths subjects with some experience will be ideal to start a data science course. Students with existing knowledge of one or more of the above units with be considered for Recognition of Prior Learning.

Assessment :

Each learner will be assessed by way of multiple choice questions at the end of the course. The candidates will also be required to create a portfolio of evidence which may include course related projects to demonstrates achievement of required knowledge of the subject.

The course is a part of continuous professional development of the candidates who are working in the related areas.

Progression :

After graduating, you will be able to utilize AI to extract data, apply data-driven intelligence to inform decisions, solve complex business challenges with cutting-edge solutions, and improve productivity and quality for small and medium-sized businesses up to the largest organizations.

Duration:

Duration of the course is appx 6 months.onths.