(All course fees are in USD)

This online is entitled to 5% off bundle discount. 

Course Description

This online course is made up of 2 introductory courses pertaining to The Digital Age:

Course 1 – Introduction to Artificial Intelligence

The Introduction to AI provides an overview of AI concepts and workflows, machine learning, deep learning, and performance metrics. You would learn the difference between supervised, unsupervised, and reinforcement learning; be exposed to use cases, and see how clustering and classification algorithms help identify AI business applications.

Course 2 – Introduction to Data Analytics

The Data Analytics course introduces beginners to the fundamental concepts of data analytics through real-world case studies and examples. You would learn about project lifecycles, the difference between data analytics, data science, and machine learning; building an analytics framework, and using analytics tools to draw business insights.

Offered in Partnership with

Simplilearn

Course Delivery

Course 1 – Introduction to Artificial Intelligence:  3.5 hours of enriched learning

Course 2 – Introduction to Data Analytics:  3 hours of online self-paced learning

Total online self-paced learning of 2 courses: 6.5 hours

This online is entitled to 5% off bundle discount. Original total fees is USD798, and after discount becomes USD758.

Benefits

Course 1 – Introduction to Artificial Intelligence

This Introduction to AI for beginners online course (3.5 hours of online learning) is ideal for developers aspiring to be AI engineers, as well as for analytics managers, information architects, analytics professionals, and graduates looking to build a career in artificial intelligence or machine learning.

Course 2 – Introduction to Data Analytics

• 3 hours of online self-paced learning
• Real-world case studies and examples

The online course caters to CxO-level and middle management professionals who want to improve their ability to derive business value and ROI from analytics.

This Data Analytics for beginners online course is also ideal for anyone who wishes to learn the fundamentals of data analytics and pursue a career in this growing field.

Skills to be Learned

Courses 1 to 2 of this comprehensive course would enable you to acquire background knowledge of 2 of the key areas required for the Digital Age, including AI, & big data.

Course 1 – Introduction to Artificial Intelligence

• Purpose of artificial intelligence technology
• Concepts of deep learning and machine learning workflow
• Supervised learning
• Semi-supervised learning
• Unsupervised learning

Course 2 – Introduction to Data Analytics

• Types of data analytics
• Frequency distribution plots
• Swarm plots
• Data visualization
• Data science methodologies
• Analytics adoption frameworks
• Trends in data analytics

Awards

Total 2 “Certificate of Achievements” for each respective course, upon successful completion of each course:

Course 1 – Introduction to Artificial Intelligence

“Certificate of Achievement” on Introduction to Artificial Intelligence from Simplilearn

Course 2 – Introduction to Data Analytics

“Certificate of Achievement” on Introduction to Data Analytics from Simplilearn

Awarding Organisation

Simplilearn

Learning Outcomes

Course 1 – Introduction to Artificial Intelligence

When you complete this Introduction to Artificial Intelligence course, you will be able to accomplish the following:

• The meaning, purpose, scope, stages, applications, and effects of AI
• Fundamental concepts of machine learning and deep learning
• The difference between supervised, semi-supervised and unsupervised learning
• Machine Learning workflow and how to implement the steps effectively
• The role of performance metrics and how to identify their key methods

Course 2 – Introduction to Data Analytics

• Understand how to solve analytical problems in real-world scenarios
• Define effective objectives for analytics projects
• Work with different types of data
• Understand the importance of data visualization to drive more effective business decisions and ROI
• Understand charts, graphs, and tools used for analytics and use them to gain valuable insights
• Create an analytics adoption framework Identify upcoming trends in data analytics

Assessments

Courses 1 to 2: Course-end assessments

Course Completion Criteria

For Both Courses 1 to 2

• Complete the self-pace learning
• Obtain 80% in the Simulation Test

Who Should Enrol

• Developers aspiring to be an Artificial Intelligence engineer or Machine Learning engineers
• Analytics managers who are leading a team of analysts
• Information architects who want to gain expertise in Artificial Intelligence algorithms
• Graduates looking to build a career in Artificial Intelligence and Machine Learning
• This course is ideal for anyone who wishes to learn the fundamentals of data analytics and pursue a career in this growing field. The course also caters to CxO-level and middle management professionals who want to improve their ability to derive business value and ROI from analytics.

Prerequisites

There are no prerequisite knowledge requirements.

Course Overview

Course1 – Introduction to Artificial Intelligence

Lesson 1 – Course Introduction

Lesson 2 – Decoding Artificial Intelligence

Lesson 3 – Fundamentals of Machine Learning and Deep Learning

Lesson 4 – Machine Learning Workflow

Lesson 5 – Performance Metrics

Course 2 – Introduction to Data Analytics

Lesson 01 – Data Analytics Overview

Lesson 02 – Dealing with Different Types of Data

Lesson 03 – Data Visualization for Decision-making

Lesson 04 – Data Science Data Analytics and Machine Learning

Lesson 05 – Data Science Methodology

Lesson 06 – Data Analytics in Different Sectors

Lesson 07 – Analytics Framework and Latest Trends

Access Period of Course

1 year from date of enrolment