Predictive Artificial Intelligence

Expand your skill set and help your organization make data-informed predictions.

Master the practical use of predictive AI to solve real business problems. This hands-on course guides you through the full analytics workflow—from data collection and preparation to building, training, and deploying predictive analytical models. Explore key techniques like feature engineering, regression, and classification through real-world cases such as credit card fraud detection. Learn to communicate results clearly, build stakeholder trust, and lead impactful, data-driven initiatives in your organization.

Throughout this course, you will

Define and deploy predictive AI with diverse data types, while assembling skilled teams to develop models that address real-world challenges.
Set KPIs to drive predictive AI initiatives and align them with business objectives. Additionally, develop a detailed predictive AI requirements document.
Utilize prediction engineering techniques to build models and extract data for practical use, while working with tools like FeatureTools and Pandas.
Transform raw data into features to enhance model accuracy using both automated and manual engineering methods, and master Featuretools to simplify the process.
Use supervised learning methods and hyperparameters to build predictive models. Assess model accuracy and interpret results with scikit-learn, XGBoost, and Pyreal.
Master data anomaly detection and apply it across sectors with unsupervised learning methods. Leverage tools like Orion to enhance model accuracy and efficiency.
Evaluate and analyze AI models considering time, personnel and costs. Additionally, track deployment progress using tools such as SHAP and Pyreal.
Assemble teams of data experts, stakeholders, and other roles to collaborate on predictive AI projects. Use data assessments, success metrics, and scaling tools.

This course is aimed at

Mid-Level to Senior Professionals in roles like data science, analytics, business intelligence, product innovation, and technology leadership/consulting across industries such as finance, healthcare, retail, tech and manufacturing.
Tech leaders, Data Engineers, and Analysts seeking to upskill or pivot into AI-driven roles.
Data Scientists and Data Engineers looking to integrate predictive analytics and AI into their workflow.
Business Intelligence Analysts wanting to move from traditional reporting to more advanced predictive modeling.
Tech and Product Managers who oversee data-driven products and want to understand predictive capabilities.
Founders or Chief Technology Officers (CTOs) or Chief Data Officers (CDOs) seeking to lead AI transformation within their organizations.

Certificate

Meet your instructor

The MIT Learning Experience

Learn through practice

Practice processes and methods through simulations, evaluations, case studies, and tools

Learn from others

Connect with an international community of professionals while working on projects based on real examples

Learn on demand

Access all online content and watch videos from anywhere

Reflect and apply

Bring the newly learned skills into your company through examples of technical work environments and good thoughtful prompts.

Show your success

Earn a Professional Certificate and 4.8 Continuing Education Units from MIT xPRO (MIT xPRO CEUs).

Learn from the best

Get training from MIT professors and industry experts

Predictive Artificial Intelligence