Artificial Intelligence And ML
Get to know who we are and also meet with some of our team.
Online, flexible schedule
Our programs are online and designed to accommodate busy schedules, and even the occasional missed week. The programs are flexible, yet with our minimum 15 hours/week requirement, they are intensive enough to prepare students well for their new career and get them job-ready in a relatively short amount of time. We offer extra help and private sessions with academic instructors for students who need a bit more support.
This course covers Artificial Intelligence (AI) and Machine Learning (ML) from foundational principles to cutting-edge applications. You'll learn how to design, build, and implement AI-driven solutions and understand the ethical considerations surrounding AI. By the end, you’ll be equipped to apply machine learning algorithms, work with large datasets, and build models that solve real-world problems in industries like healthcare, finance, and technology.
What you’ll study
In this course, you will study a wide range of topics including the foundations of AI, such as data preprocessing, feature engineering, and model selection. You'll delve into the mathematical concepts behind machine learning algorithms like linear regression, logistic regression, decision trees, and neural networks. You’ll also explore advanced topics, such as deep learning architectures, natural language processing (NLP), reinforcement learning, and AI ethics, providing you with skills to create and evaluate complex AI systems.
Entry requirements
- A working laptop or desktop computer with a minimum of 4GB RAM
- A stable internet connection with a minimum speed of 5 Mbps
- An up-to-date web browser (Chrome, Firefox, or Safari)
- Access to video conferencing software (e.g., Slack or Zoom)
How you'll be taught
This course will be delivered through interactive online sessions, with live demonstrations, hands-on projects, and guided assignments to develop practical skills in AI and ML.
Fees and funding
To enroll in the course, a one-time payment of £3000 is required. Alternatively, you can opt for an installment payment plan, consisting of three payments: 50% of the total cost upfront, followed by two equal payments of 25% each. Please contact us to discuss the installment plan details.
Careers and employability
Equipped with a solid grounding in AI and ML, you'll be ready to pursue roles such as AI Engineer, Data Scientist, Machine Learning Specialist, NLP Engineer, and more in sectors like tech, healthcare, finance, and education.
Syllabus
- Introduction to Artificial Intelligence
- Understanding Data Science Basics
- Data Preprocessing and Feature Engineering
- Introduction to Probability and Statistics for Machine Learning
- Supervised Learning: Linear and Logistic Regression
- Unsupervised Learning: Clustering Algorithms (K-means, Hierarchical)
- Introduction to Neural Networks and Backpropagation
- Advanced Neural Networks and Deep Learning (CNNs, RNNs)
- Natural Language Processing Fundamentals
- Natural Language Processing (Advanced Topics, Sentiment Analysis, NLP Models)
- Image Recognition and Computer Vision Basics
- Deep Reinforcement Learning and Decision-Making Algorithms
- AI Ethics and Responsible AI Deployment
- Advanced Data Wrangling Techniques
- Model Deployment and Monitoring with Cloud AI Services
- Introduction to Time Series Analysis and Forecasting
- Data Visualization Techniques for ML
- Feature Selection and Dimensionality Reduction (PCA, t-SNE)
- Hyperparameter Tuning and Model Optimization Techniques
- Building and Deploying APIs for ML Models
- Introduction to Transfer Learning
- Exploring AI in Edge Computing and IoT
- Collaborative Filtering and Recommendation Systems
- Capstone Project: Developing a Comprehensive AI Solution
How to apply
- You must provide accurate and complete information during the registration process.
- You must complete the payment process to successfully enroll in the course.
- Follow the instructions received in the email to access the course materials or live session.
Where our graduates work
What our graduates say
Don’t just take our word for it, hear from our students themselves
Lucas Turner
@lucasturner
Completing the program was life-changing! The hands-on projects prepared me for real-world scenarios, and I landed a job within weeks.
Hannah Scott
@hannahscott
A fantastic experience with knowledgeable instructors and comprehensive modules. A bit fast-paced, but highly rewarding.
Benjamin Green
@benjamingreen
This course exceeded my expectations! The support and career guidance helped me secure my dream role in tech.
Lily Carter
@lilycarter
From coding basics to advanced topics, this course covered it all. I feel confident and prepared for my career in development.
Ethan Perez
@ethanperez
Great curriculum with real-world projects. Some areas could use more depth, but overall an amazing foundation.
Zoe Anderson
@zoeanderson
The mentorship was incredible! My mentor was with me every step of the way, and I felt well-prepared for job applications.
Mason Walker
@masonwalker
I can’t recommend this enough! The blend of theory and practice made learning easy and enjoyable. Best investment I made.
Ella Rivera
@ellarivera
Solid course with excellent resources. The projects helped me build my portfolio, which played a big role in landing a job.
Jack Thompson
@jackthompson
This course made me industry-ready. I secured a DevOps role shortly after graduation thanks to the in-depth labs and exercises.
Frequently Asked Questions
Here are some of the most common questions we get asked. If you have a question that isn't answered here, feel free to reach out to us.
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