Course Overview
Course Overview:
The "Build Predictive AI Solutions using LLM" course offers a comprehensive, hands-on experience for students to design, build, and deploy advanced predictive AI solutions. Participants will delve into the integration of generative techniques, such as Large Language Models (LLMs), with predictive modeling, covering key areas like data engineering, feature discovery, AutoML, model evaluation, and deployment on target platforms. The course includes a variety of class exercises that reinforce these concepts, allowing students to apply their knowledge effectively within capstone projects. The hands-on approach ensures that participants gain deep expertise, culminating in a Credly certification that validates their skills in this advanced field.
Student Profile:
This course is ideal for AI professionals, data scientists, and developers who are looking to expand their capabilities in predictive AI and gain experience with cutting-edge technologies like LLMs. It is particularly suited for those interested in applying their skills in practical, real-world scenarios through capstone projects.
Prerequisites:
To enroll in this course, students must have completed foundational courses in Data Science Methodology and Prompt Engineering. These prerequisites ensure that participants have the essential background knowledge needed to engage with the advanced concepts and challenges presented in this course.
Course Objectives
· Theoretical Foundations: Establish a comprehensive understanding of Generative and Predictive AI principles, focusing on LLMs for content creation. Grasp the methodologies behind Predictive AI, enabling accurate future event forecasting.
· Design and Develop a Predictive solution: Learn how to develop a Predictive AI solution in your Capstone project
· Capstone Project: Synthesize course learnings by undertaking a Capstone project that addresses different use cases like Health Equity, Loan Approval using AI. Investigate the transformative impact of AI in real-world business scenarios, with a spotlight on Health Equity Analytics.
· Deploy your Capstone solution: Understand how to integrate with other technologies – AI and non-AI and deploy in a MS Azure cloud environment
· Work Individually or in a Group: Work individually as well as in a group to enhance your learning
Expected Outcome
Upon course completion, participants will be equipped to:
· Proficiently Deploy AI: Demonstrate expertise in utilizing Generative AI for content curation and Predictive AI for insightful analytics and projections.
· Course Material: Receive lecture materials & tips on Generative and Predictive AI
· Practical Project Execution: Present a Capstone project critiqued by field experts, meriting potential accolades and recognition.
· Solution Accelerators: Receive a set of generative and Predictive AI accelerators for future use.
· Certified Skills: Obtain a “Credly” completion certificate as an accomplishment.
Through this journey, students will not only grasp the theoretical constructs of AI but also their practical deployment, setting the stage for a dynamic career in an AI-driven business environment.
Capstone Project
The capstone project will involve two use cases, with HR Analytics demonstrating Generative AI's capabilities and Health Equity showcasing Predictive AI's capabilitiesan image.
Use Case - HR Analytics
Utilize HR Analytics use case to explore how to analyze and rank a set of resumes or match a resume against job board posting
Use Case - Health Equity
Use Health Equity to analyze social, economical or health vulnerability data to develop Health equity score for a given county
Learning through Videos
Pre-recorded Videos will provide you concepts and examples associated with Generative AI or Large Language Model (LLM).
No New Set-Up Needed
All the development environment will be provided by Applied AI Institute in a secure Microsoft Azure cloud environment. In addition all solution accelerators associated with various use case will be provided by Applied AI Institute.
Knowledge Checks with Final Assignment
As you learn a concept, test your understanding using Interactive Knowledge Checks or quizzes
We will also test how you apply all learnt concepts using a Final Assignment based upon you individual home-work assignment.
Live Lectures
Engage in 16-20 hours of recorded lectures
- Lecture 1: Use case Capstone Project definition
- Lecture 2 : Data Engineering & Descriptive Analytics
- Lecture 3: Feature Engineering
- Lecture 4: Model Development
- Lecture 5: Model Testing and Evaluation
- Lecture 6: Model Deployment and Monitoring
Homework Assignments
To complement these lectures, you will receive homework after each lecture:
1. Use Case Definition
2. Generative AI - Prompt Engineering & Knowledge Classification
3. Predictive AI - Techniques
4. Design Predictive AI Solution
5. Prototype Generative AI
6. Prototype Predictive AI
7. Test and Measure
8. Complete Capstone Project
Credly Certification
Students will be asked to complete homework assignment at the end of each lecture. Upon successful completion of homework assignment and final project, students will receive a Credly certification of completion for adding into their profile.
Course Registration
To enroll in the course, please select "Enroll now" button below. If you have been given a coupon, you can apply it on the enrollment page.
Curriculum
AAII Course Offerings
In our AI series, we have designed many courses on AI related topics such as Vision, Conversational AI, Graph AI and Data Science. We are working with a few universities in launching these courses. These courses are aimed as education aid for graduate level courses at leading US universities. We will be releasing these courses on a periodic basis using Teachable as a platform. Please select "View All Products" to view all our courses.
