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Foundation of Artificial Intelligence & Machine Learning
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Program
Foundation of Artificial Intelligence & Machine Learning
Leap ahead in your learning and dive into the world of artificial intelligence (AI) and machine learning (ML). Set yourself up for future success in these fast-growing, cutting edge technologies.
Flexible + Live Classes
Beginner Level
Mentor Support
Ever wonder how your favourite streaming service, like Netflix, recommends exactly what you'd like to watch? That's the magic of artificial intelligence (AI) and machine learning (ML) working to make you happy. And these clever technologies will soon be shaping your life in thousands of other ways too.
Imagine how ML could track your game-playing style and help your gaming console make games more exciting. Or imagine AI creating a robot that tidies your bedroom!
The more you look around, the more youll see how AI and ML could soon be touching your world... and YOU could be someone creating these ideas as well.
Want to jump in and get involved NOW?
If you like the thought of leaping ahead of your classmates and learning about AI and ML before they do, our Foundations of Artificial Intelligence and Machine Learning program is tailor-made for you.
Whether you are passionate about science, sport, art, music, or business... you can have fun building fantastic skills in AI and ML that will set you up for the next stage of your education.
You'll dive into Python, one of the most popular programming languages behind AI's magic. You'll use Python to build structures, make decisions, loop through challenges, and sort out problems. Itll be like building your own digital gadgets.
Youll also get more technical with Python's special libraries, pandas and NumPy, and you'll turn data into stunning graphs that can tell stories better than any book.
You'll step into the shoes of an AI detective, learning to distinguish between the good and the bad supervised and unsupervised learning. And youll build your own superpowers in understanding patterns and making predictions.
Plus, youll explore real-life examples of how AI and ML are shaping our world from song suggestions to robots to self-driving cars.
And the best part is, you won't just be learning boring theories. You'll be using some of the technologies yourself in fun hands-on labs. So, by the end of the program, youll be on your way to becoming a tech maestro, armed with skills that will make you stand out in any crowd.
If youre ready to unleash your tech-savvy side and leap ahead of your classmates, grab this fantastic opportunity to dive into the world of AI and ML. We cant wait to guide you every step of the way as you take this exciting learning journey.
This program comprises 6 courses that take you on a carefully defined learning journey.
Our proven learning methodology blends the best that instructor-led training and self-paced learning have to offer. Leveraging the power of instructor feedback, mentor-supported hands-on practice, and additional home-based studying, you will start to build both a technical and a practical understanding of AI and machine learning.
Additionally, you will enjoy learning via an interactive online classroom environment where you will be able to participate and actively engage with your peers, instructors, and mentors.
The materials for modules are accessible from the start of the program and will remain available for the duration of your enrollment. Materials include videos, hands-on labs, exercises, and knowledge checks.
Enrollment in the program includes all 6 courses. You cannot enroll for the courses separately.
As part of our mentoring service you will have access to valuable guidance and support throughout the program. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.
Once you have successfully completed the program, you will earn your Certificate of Completion.
You will have:
- An understanding of AI trends and career opportunities.
- Knowledge of how AI is impacting businesses.
- Practical understanding of Python as an AI tool.
- Knowledge of how to create data visualizations using Python.
- Practical understanding of the different forms of graphs.
- An understanding of how statistics impacts AI research.
- An understanding of the basics of SQL and data structures.
- An understanding of machine learning terms, libraries, and the languages used to create them.
- The abiliity to apply the appropriate form of regression to a data set for estimation.
- The ability to apply an appropriate classification method for a particular machine learning challenge.
- The ability to use the correct clustering algorithms on different data sets.
- Be able to explain how recommendation systems work, and implement one on a data set.
- Have demonstrated your understanding of machine learning in an assessed project.
Learners who want to:
- Explore the magic behind smart devices, virtual assistants, and more.
- Discover the answers to questions like: How does Siri understand my voice commands, how does Netflix recommend shows I might like, etc.
- Solve real-world problems such as predicting climate patterns, disease detection, and more in creative ways.
- Shine in their education and get ahead of their classmates.
- Pursue rewarding careers in the future whatever their interest - sports, finance, entertainment, medicine, business, and more.
There are no prerequisites for this program
Program Outline
Course Introduction
Program Syllabus
Grading Scheme
Lab Installation - Jupyter Labs
Final Exam Instructions
Reading: Module Introduction
Reading: The Evolution and Definition of AI
Reading: Early AI Technology
Reading: AI Pioneers
Infographic: AI Timeline and Famous Applications
Reading: Current AI Tech and Trend-setters
Reading: Key AI Concepts and Terminology
Reading: Opportunities and Occupations in AI
Video - Why Study Artificial Intelligence?
Exam 1.1 - 4 Questions
Reading: Module Introduction
Reading: The Difference Between Narrow, General, and Super AI
Exam 1.2 - 4 Questions
Reading: Module Introduction
Reading and Lab: Application of AI Across Industries
Reading: AI in Video and Image Processing
Reading and Lab: Uses of AI in Speech Processing and Intelligent Bots
Exam 1.3 - 4 Questions
Reading: Module Introduction
Reading: Opportunities in AI Across Industries
Reading: Basics of Deep Learning and Advanced Analytics
Reading: The Coming Ethical and Legal Issues Associated with AI
Exam 1.4 - 4 Questions
Reading: Module Introduction
Reading: Principles of Machine Learning
Video: What is Machine Learning?
Reading: Machine Learning Model
Video: Classification and Regression in Machine Learning
Exam 1.5 - 4 Questions
Final Exam - 15 Questions
Reading: Introduction to Database Concepts
Reading: Learning Objectives
Module 2.1 Exam - 3 Questions
Module 2.2 Lab Exercises
Reading: SQL Relational Database Models
Reading & Video: Types of SQL Relationships
Reading: Data Types and Data Formats
Lab: Define and Describe NoSQL Databases
Module 2.2 Exam - 8 Questions
Module 3 Lab Exercises
Reading: Selecting and Retrieving Data from a SQL Database
Reading & Labs: Filtering, Sorting and Calculating Data
Reading and Lab: Building Joins
Lab: Using Python for Data Acquisition and Analysis
Module 2.3 Exam - 5 Questions
Final Exam - 20 Questions
Reading: Python Course Introduction
Reading & Video: Advantages of Python in AI
Reading: Data Types
Video - Data Types
Lab: Data Types in Python
Reading: Understand and Define Fundamental Data Structures
Lab: Understand and Define Fundamental Data Structures
Reading: Implement and Apply Data Structures
Lab: Implement data structures
Exam 3.1 - 5 Questions
Reading: Basic Python Programming Introduction
Reading: String Operations
Lab - Strings in Python
Video - Data Structures
Reading: Demonstrate Lists and Tuples
Video: Demonstrate Lists and Tuples
Lab: Demonstrate Lists and Tuples
Reading: Operators
Lab: Operators and Operations
Reading: Demonstrate Conditions, Branching
Lab: Demonstrate Conditions and Branching
Reading: Loops - for,while
Lab: For Loops and While Loops
Reading: Functions, Classes, Objects
Lab: Functions, Classes, and Objects
Basic Python Scripts
Pandas and Numpy
Hands-on Lab - Pandas
Hands-on Lab - Numpy
Exam 3.2 - 5 Questions
Reading: Algorithms Module Introduction
Reading: Understand and Define Sorting Algorithms
Reading: Create and Apply Algorithms
Module 3.3 Exam - 4 Questions
Reading: Sorting Algorithms Module Introduction
Reading: Sorting Algorithms
Jupyter Notebook Labs: Quick Sort
Jupyter Notebook Labs: Insertion Sort
Exam 3.4 - 3 Questions
Reading: Searching Algorithms Module Introduction
Searching Algorithms
Jupyter Notebook Labs: Linear Search
Jupyter Notebook Labs: Binary Search
Exam 3.5 - 3 Questions
Reading: Geographic and Graphing Algorithms Module Introduction
Reading: Geometric Algorithms
Final Exam - 10 Questions
Reading: AI Statistics - Python Introduction
Reading: Getting Started with Cognos
Reading: Basic Statistic Concepts
Exam 4.1 - 3 Questions
Reading: Descriptive Statistics Introduction
Reading: Define and Demonstrate Descriptive Statistics
Hands-on Lab - Calculating central values
Reading: Define and Demonstrate Probability
Reading: Define and Demonstrate Correlation
Hands-on Lab - Correlation of Data
Reading: Define and Demonstrate Linear Regression
Reading: Describe Basic Statistical Analysis Tools
Reading: Descriptive Statistics Summary
Hands-on lab - Using plotly with built-in data
Exam 4.2 - 5 Questions
Final Exam - 10 Questions
Reading: Data Visualization Fundamentals Course Introduction
Reading: Understand and Define Simple Data Visualizations and Graph Types
Reading: Identify Popular Visualization Dashboards
Exam 5.1 - 4 Questions
Reading: Module Introduction
Reading: Define and Describe Basic Visualization Tools
Reading: Define Specialized Visualization Tools
Reading: Describe Creating Maps and Visualizing Geospatial Data
Exam 5.2 - 4 Questions
Reading: Module Introduction
Reading: Introduction to Building Charts
Lab: Build Pie Chart
Lab: Build Line Chart
Lab: Build Bar Chart
Lab: Build Column Graph
Lab: Build Ring Plot
Lab: Build Map Graph
Reading: Course Conclusion
Exam 5.3 - 4 Questions
Final Exam - 10 Questions
Introduction
Learning Objectives
Welcome
Introduction to Machine Learning
Python for Machine Learning
Supervised vs Unsupervised
Introduction
Learning Objectives
Introduction to Regression
Simple Linear Regression
Model Evaluation in Regression Models
Evaluation Metrics in Regression Models
Lab: Simple Linear Regression
Multiple Linear Regression
Lab: Multiple Linear Regression
Non-Linear Regression
Lab: Polynomial Regression
Lab: Non-linear Regression
Introduction
Learning Objectives
Introduction to Classification
K-Nearest Neighbors
Evaluation Metrics in Classification
Lab: KNN
Introduction to Decision Trees
Building Decision Trees
Lab: Decision Trees
Intro to Logistic Regression
Logistic Regression vs Linear Regression
Logistic Regression Training
Lab: Logistic Regression
Support Vector Machine
Lab: SVM (Support Vector Machines)
Introduction
Learning Objectives
Introduction
Learning Objectives
Final Exam - 10 Questions
Instructions
Final Exam - 30 Questions
Earn your certificate
Once you have completed this course, you will earn your certificate.
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Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
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FAQs
This Foundations of Artificial Intelligence and Machine Learning program can offer you numerous benefits:
- Skills Development: The program will provide you with a solid foundation in AI and machine learning concepts, algorithms, and tools. This skill set is in high demand across all industries.
- A Future-Proof Career: AI and machine learning are shaping the future of technology. By gaining knowledge in these areas early on, you'll be better prepared to adapt to changing job requirements and industry trends.
- Interdisciplinary Knowledge: AI and machine learning intersect with numerous fields, from computer science and engineering to healthcare, sport, business, finance, and even creative arts.
- Problem-Solving Skills: AI and machine learning involve tackling complex problems and designing innovative solutions. Participating in this program will enhance your critical thinking and problem-solving skills, which are invaluable in any career.
- Continuous Learning: The field of AI and machine learning is rapidly evolving. Completing a foundational program can establish a habit of continuous learning, keeping you updated with the latest developments and trends.
Of course not! This program is designed in a way that you wont have to skip your regular classes in school. The program covers a total of 60 hours of training through a mix of self-paced and instructor-led learning. We therefore recommend that you prepare to dedicate 2-3 hours each week to the program.
While all the job roles within cloud computing are in high demand, there are some roles that are in more demand by employers than others. According to Glassdoor, the most in-demand cloud computing job role is cloud administrator. This is followed by cloud support engineer, cloud security analyst, cloud network engineer, cloud software engineer, cloud automation engineer, cloud engineer, cloud consultant, cloud data scientist, and cloud architect.
The program will be taught by experienced instructors who specialize in making technical concepts accessible and engaging for young learners.
Yes. Foundations of Artificial Intelligence and Machine Learning program is 100% online. You will not be required to attend any classes in person. However, please note you will need appropriate access to the internet and the required technology to be able to use the program materials and participate in the live virtual instructor-led classes. The materials are in the form of articles, videos, and knowledge checks.
This means you can access this program wherever you live. And the great news is that you won't be learning alone. You will be encouraged to connect with other learners and mentors through the program discussion space.
Yes, youll be introduced to Python during the program. Once you complete the program, youll have learnt the basic functioning of this highly popular AI programming language.
We archive the live sessions included in the program and make them available on the learning management system (LMS). Therefore, if you miss a session, dont worry! You will be able to see the recording of it in the LMS. The recordings will be accessible throughout the remainder of the program.
To attend live video streaming sessions, view session recordings, and access learning materials, you can use your mobile phone. A smartphone that is 4G enabled is required. However, to do the hands-on labs and practicals, you will need a PC/laptop.
Type of certificate
Certificate of completion
About this program
06 Courses
10 Skills
Includes
Discussion space
45 Hands-on labs
18 Videos
18 Quizzes
06 Course exams
01 Final exam
Create
Jupyter Notebook
Data analyzing project
Future prediction model
Exercises to explore
MongoDB - SQL & NoSQL
Regression
Classification
Clustering
Recommender systems
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