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AI-ML Projects for Data Professionals

New
·

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

Google
Axtria
Massachusetts Institute of Technology
UT Austin
University of Cincinnati

Course overview

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 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!

Who is this course for

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.

What you’ll get out of this course

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.

This course includes

20 interactive live sessions

Lifetime access to course materials

20 in-depth lessons

Direct access to instructor

11 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.

Course syllabus

Expand all modules

  • Week 1

    May 12

    Week dates are set to instructor's time zone

    Events

    • May

      12

      Machine Learning Foundations

      Sun, May 12, 3:00 PM - 4:00 PM UTC

    • May

      12

      DS Workflow & Github Setup

      Sun, May 12, 4:00 PM - 4:30 PM UTC

    • May

      12

      Case Study 1: Problem Walkthrough

      Sun, May 12, 4:30 PM - 5:00 PM UTC

    Modules

    • Week 1: Learning the Basics

  • Week 2

    May 13—May 19

    Week dates are set to instructor's time zone

    Events

    • May

      17

      [Optional] Office Hour

      Fri, May 17, 12:30 AM - 1:00 AM UTC

    • May

      19

      [Case Study 1] Uber ETA Prediction Problem Scoping

      Sun, May 19, 3:00 PM - 3:30 PM UTC

    • May

      19

      [Case Study 1] Uber ETA Prediction Code Review

      Sun, May 19, 3:30 PM - 4:00 PM UTC

    • May

      19

      [Case Study 1] Model Deployment in Streamlit

      Sun, May 19, 4:00 PM - 4:30 PM UTC

    • May

      19

      Case Study 2: Problem Walkthrough

      Sun, May 19, 4:30 PM - 5:00 PM UTC

    Modules

    • Week 2: [Case Study 1] Uber ETA Prediction

  • Week 3

    May 20—May 26

    Week dates are set to instructor's time zone

    Events

    • May

      24

      [Optional] Office Hour

      Fri, May 24, 12:30 AM - 1:00 AM UTC

    • May

      26

      [Case Study 2] Demand Forecasting Problem Scoping

      Sun, May 26, 3:00 PM - 3:30 PM UTC

    • May

      26

      [Case Study 2] Demand Forecasting Code Review

      Sun, May 26, 3:30 PM - 4:30 PM UTC

    • May

      26

      Case Study 3: Problem Walkthrough

      Sun, May 26, 4:30 PM - 5:00 PM UTC

    Modules

    • Week 3: [Case Study 2] Demand Forecasting

  • Week 4

    May 27—Jun 2

    Week dates are set to instructor's time zone

    Events

    • May

      31

      [Optional] Office Hour

      Fri, May 31, 12:30 AM - 1:00 AM UTC

    • Jun

      2

      [Case Study 3] Speech-to-Text Problem Scoping

      Sun, Jun 2, 3:00 PM - 3:30 PM UTC

    • Jun

      2

      [Case Study 3] Speech to Text Code Review

      Sun, Jun 2, 3:30 PM - 5:00 PM UTC

    Modules

    • [Case Study 3] Transformer Based Speech Transcription

  • Week 5

    Jun 3—Jun 9

    Week dates are set to instructor's time zone

    Events

    • Jun

      7

      [Optional] Office Hour

      Fri, Jun 7, 12:30 AM - 1:00 AM UTC

    • Jun

      9

      Github Portfolio Review

      Sun, Jun 9, 3:00 PM - 4:00 PM UTC

    • Jun

      9

      Website Setup

      Sun, Jun 9, 4:00 PM - 4:30 PM UTC

    • Jun

      9

      Showcase Your Work

      Sun, Jun 9, 4:30 PM - 5:00 PM UTC

    Modules

    • Week 5: Build Your Portfolio

  • Post-Course

    Events

    • Jun

      14

      [Optional] Office Hour

      Fri, Jun 14, 12:30 AM - 1:00 AM UTC

What people are saying

        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

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

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

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

Indu Seetharaman

Data Scientist, Frost Bank

Meet your instructor

Manisha Arora

Manisha Arora

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.

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Join an upcoming cohort

AI-ML Projects for Data Professionals

Cohort 1

$1,250 USD

Dates

May 12—June 9, 2024

Payment Deadline

May 12, 2024
|

Bulk purchases

Course schedule

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.

Free resource

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

Learning is better with cohorts

Learning is better with cohorts

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

Frequently Asked Questions

What happens if I can’t make a live session?
I work full-time, what is the expected time commitment?
What’s the refund policy?
A pattern of wavy dots
Join an upcoming cohort

AI-ML Projects for Data Professionals

Cohort 1

$1,250 USD

Dates

May 12—June 9, 2024

Payment Deadline

May 12, 2024
|

Bulk purchases

$1,250 USD

5 Weeks

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