Accelerate Your Future: Unleash the power of AI and Machine Learning in our Immersive Bootcamp

AI is all around us - there is no better time to gain key skills in the this transformative industry!

Our daily lives are increasingly shaped by artificial intelligence, and many of the applications we use are powered by AI and machine learning. This is leading many industries and countries to invest in artificial intelligence technologies, creating exciting career opportunities.

This bootcamp will increase your knowledge and prepare you for full-time and freelance jobs in diverse industries that are adopting AI and machine learning. You will be able to relate your prior education and experience to authentic and relevant programming projects while learning in a game-based environment. Experience hands-on lessons in solving simple and complex real-world problems across different industries that may include retail, finance, tech, and health care.

Gain in-demand programming skills that will allow you entry into the world of machine learning, AI and deep data analytics. Techniques learned in this program will allow you to use data sources to make informed decisions that yield real improvements in growth, efficiency, and cost-savings across all industry sectors.

Complete the program with an experiential learning capstone project where you will learn about freelance coding projects and complete a small freelance coding assignment.

Course details

Discover how machine learning is used to create models that understand large amounts of data. Learn to use Python libraries for predictive problems (supervised learning) and for data clustering problems (unsupervised learning).

Study major machine learning techniques such as multiple linear regressions (Ridge and Lasso), generalized linear models and classification, and clustering and dimensionality reduction methods.

Technologies you will learn: 

Data analytics

• Python for Data Analysis and Visualization
• Pandas
• Matplotlib
• Seaborn
• Jupyter Notebook
• GitHub

Predictive analytics

• Classical Machine Learning
• Deep Learning
• Computer Vision (CV)
• Natural Language Processing (NLP)
• scikit-learn
• Tensorflow

What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, such as learning from experience, reasoning, problem-solving, and decision-making. AI systems can process and analyze large amounts of data, adapt to new information, and improve their performance over time.

These technologies encompass various subfields, including machine learning, natural language processing, computer vision, and robotics, and hold the potential to revolutionize industries, enhance automation, and advance scientific understanding.

What is Machine Learning?

Machine Learning (ML) is a subset of artificial intelligence that focuses on developing algorithms and models that enable computers to learn from data and improve their performance on specific tasks over time. Instead of being explicitly programmed, ML systems use patterns and insights from large datasets to make predictions, decisions, or classifications.

This iterative process involves the system adjusting its parameters based on examples, allowing it to generalize and make accurate predictions on new, unseen data. Machine learning has applications in various fields, from image and speech recognition to recommendation systems and medical diagnoses.

The Machine Learning and Artificial Intelligence Bootcamp

The Machine Learning and Artificial Intelligence Bootcamp includes virtual face-to-face instruction and practical hands-on lessons delivered using an interactive learning system powered by RoboGarden. The RoboGarden platform teaches coding literacy by guiding users through a sequence of interactive challenges built using a game-based methodology.

Learners will benefit from instructors and teaching assistants selected for their teaching ability, leading-edge skills, and experience. Students will have 24/7 access to course materials, allowing them to save their progress and resume at any time.

Ten modules use game-based, case-based, and practice-based instruction ensuring an interactive and experiential training experience.

Module 1             Fundamentals of Python Development

Module 2             Data Analysis with Python

Module 3             Classical Machine Learning 1

Module 4             Classical Machine Learning 2

Module 5             Complete Classification of Classical Machine Learning

Module 6             Modern Machine Learning 1

Module 7             Modern Machine Learning 2

Module 8             A Complete Application of Modern Machine Learning

Module 9             Portfolio Builder

Module 10           Learn to Earn

Prefer an introduction to machine learning before committing to the Bootcamp? Check out our Machine Learning Foundation course.