5 Weeks
·Cohort-based Course
Gain hands-on experience and build a portfolio of industry AI/ML projects. Scope & execute the workflow from data exploration to deployment.
5 Weeks
·Cohort-based Course
Gain hands-on experience and build a portfolio of industry AI/ML projects. Scope & execute the workflow from data exploration to deployment.
10+ Years Industry Experience at
Course overview
If you want to succeed as a Data Scientist in tech, proficiency in 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 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
Course Curriculum:
Week 1: Scoping ML Projects, Stakeholder Buy-In Strategies, and Data Science Workflow on Git
Week 2: Data Cleaning, Feature Engineering, ML algorithms, Deployment on Streamlit
Week 3: Ensemble Models, Forecasting Methods, ML Tradeoffs, Actionable Insights, Coding Best Practices
Week 4: Model Deployment on Cloud, Coding Best Practices, Github Portfolio Showcase
Week 5: Project Discussion, Set up Portfolio, Build your Website, Showcase your Work
Pre-requisites:
1. Familiarity with R / Python programming language
2. Knowledge of data manipulation using Pandas
3. Understanding of machine learning fundamentals is good-to-have
4. Learning curiosity 🙂
Time-commitment:
8-10 hours per week
Class Format:
Each 2-hour session will feature 1.5 hours of content-rich instruction followed by 30 minutes of open discussion and Q&A. Prior to each class, you will be expected to engage in pre-readings, hands-on exercises, and GitHub submissions. During sessions, we'll explore various problem-solving techniques, address nuances and trade-offs, and derive actionable insights to drive business objectives forward.
Bonus Features:
In addition to course content, you will have the opportunity to showcase your best projects weekly on the PrepVector Newsletter and LinkedIn page. Outstanding projects will also receive special recognition on LinkedIn by me!
01
Data scientists who want to build a compelling portfolio of industry projects to showcase their skills to potential employers.
02
Software and data engineers eager to gain expertise in applications of machine learning methodologies to enhance their technical repertoire.
03
Data and BI analysts seeking to acquire hands-on experience in leveraging data-driven insights to solve industry challenges.
Master Practical Applications of Machine Learning Methodologies
Gain hands-on experience in applying machine learning methodologies to real-world industry scenarios. Learn how to process data effectively, select the right algorithms, and implement models for accuracy and efficiency.
Implement End-to-End Data Science Projects & Deploy on Cloud
Develop a structured approach to navigating complexities of scoping ML projects, understanding business problems, gathering requirements, implementing projects, and deploying them on Cloud.
Build a Compelling Portfolio of Industry Projects using Organized Workflows on GitHub
Construct a portfolio of industry projects using engineering best practices, that showcase your ability to develop projects through organized workflows and coding best practices on GitHub.
Drive Actionable Insights for Informed Decision-Making
Extract meaningful insights from data and translate them into actionable recommendations for decision-makers. Explore techniques for visualizing and communicating data-driven insights, enabling informed decision-making and driving business growth.
Enhance Cross-Functional Collaboration and Communication
Collaborate effectively with diverse stakeholders, including technical and non-technical members. Hone your communication skills to frame narratives, convey complex technical concepts in a compelling and impactful manner, fostering collaboration and alignment.
20 interactive live sessions
Lifetime access to course materials
In-depth lessons
Direct access to instructor
Projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
AI-ML Projects for Data Professionals
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Abhigna Pebbati
Ketki Sharma
Vedhanarayan Ravi
Indu Seetharaman
Data Science Lead, Google | Founder, PrepVector | MIT, UT Austin & Univ of Cincinnati
I am a seasoned Data Science professional with 10+ years of experience leading data science teams and driving business growth through data-driven decision making.
I am passionate about democratizing data science and enabling others level up in their careers. I found PrepVector to enable aspiring professionals to excel in there data science careers. I have taught 350+ data professionals through my courses at Maven & PrepVector.
Be the first to know about upcoming cohorts
8-10 hours per week
Live Sessions: Sundays
11:00am - 1:00pm EST
We will meet every Sunday to discuss the weekly updates and review codes. You will get to work together with other learners in the course and learn from them.
[Optional] Office Hours: Thursdays
8:30pm - 9:00pm EST
Optional office hours once a week to answer any questions as you digest the content and work on your project.
Weekly projects
6-8 hours per week
Take time to work on the project as per the instructions provided for each week. These projects will be discussed during our live sessions.
Assess Your Data Science Skills
Unlock your potential with our self-assessment tool!
Answer a few questions to uncover your strengths, pinpoint areas for improvement, and benchmark yourself against peers. Receive personalized resources to help you up-level yourself as a data scientist.
Try it Out
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
Be the first to know about upcoming cohorts