AI-ML Projects for Data Professionals
Manisha Arora
Data Science Lead, Google
Siddarth Ranganathan
Director of Data Science, Microsoft
Become a Data Science Expert by Implementing End-to-End AI/ML Projects
If you want to succeed as a Data Scientist in tech, proficiency in AI / ML concepts is just the beginning. To truly thrive, you must implement end-to-end projects, integrate business acumen, and effectively collaborate with stakeholders. This advanced course is designed to equip mid-senior career professionals to drive impact while building a portfolio of applied AI & ML projects.
This course offers a dynamic blend of technical expertise and real-world business challenges. Through a series of interactive sessions, discussions, and hands-on projects, you will learn how to:
1) Scope machine learning projects effectively
2) Lead discussions with stakeholders to align on project objectives and get buy-in
3) Navigate the entire data science workflow from data exploration to model deployment
4) Communicate project insights and business impact to stakeholders
What you’ll learn
Gain hands-on experience and build a portfolio of industry AI/ML projects. Scope & execute the workflow from data exploration to deployment.
Scoping ML Projects, Stakeholder Buy-In Strategies, and Data Science Workflow on Git
Data Cleaning, Feature Engineering, ML algorithms, Deployment on Streamlit
Agentic AI and Frameworks, Ensemble Models, Forecasting Methods, ML Tradeoffs, Actionable Insights, Coding Best Practices
Model Deployment on Cloud, Coding Best Practices, Github Portfolio Showcase
Project Discussion, Set up Portfolio, Build your Website, Showcase your Work
Learn directly from Manisha & Siddarth
Manisha Arora
Data Science Lead, Google | UT Austin & Univ of Cincinnati
Siddarth Ranganathan
Director of Data Science, Microsoft | Founder, PrepVector | USC Marshall
Who this course is for
Data scientists who want to build a compelling portfolio of industry projects to showcase their skills to potential employers.
Software and data engineers eager to gain expertise in applications of machine learning methodologies to enhance their technical repertoire.
Data and BI analysts seeking to acquire hands-on experience in leveraging data-driven insights to solve industry challenges.
What's included
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Course syllabus
19 live sessions • 20 lessons • 10 projects
Week 1
Jan
25
Machine Learning Foundations
Jan
25
DS Workflow & Github Setup
Jan
25
Case Study 1: Problem Walkthrough
Week 1: Learning the Basics
Week 2
Jan
30
[Optional] Office Hour
Feb
1
[Case Study 1] Uber ETA Prediction Problem Scoping
Feb
1
[Case Study 1] Uber ETA Prediction Code Review
Feb
1
[Case Study 1] Model Deployment in Streamlit
Feb
1
Case Study 2: Problem Walkthrough
Week 2: [Case Study 1] Uber ETA Prediction
Schedule
Live sessions
2 hrs / week
Sun, Jan 25
4:00 PM—5:00 PM (UTC)
Sun, Jan 25
5:00 PM—5:30 PM (UTC)
Sun, Jan 25
5:30 PM—6:00 PM (UTC)
Projects
3-5 hrs / week
Async content
1-3 hrs / week
Testimonials
- I have learnt more from Manisha through her courses than I have learnt in my 4-year college degree. I wish I had found her earlier.
Abhigna Pebbati
Analytics & Data Science Manager, Meta - I attended PrepVector's Product Data Science course and it was immensely helpful in developing a thought process for approaching open ended problems. Manisha was very supportive and advised me throughout my upskilling journey. I highly recommend her course."
Ketki Sharma
Data Scientist, Dropbox - I learnt from Manisha about how to think about problems in a structured manner. This helped me not just in my interviews as a candidate but also as an interviewer. The thought process developed in her course now helps me evaluate candidates better.
Vedhanarayan Ravi
Data Scientist, Adobe - Manisha's mentorship combined with well structured program and active discussions of practical case studies, played a significant part in elevating my approach and delivery of data science projects. She fostered a supportive, safe and inclusive environment that elevated the quality of discussions. It is a great course to level up your DS skills.
Indu Seetharaman
Data Scientist, Frost Bank
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