Master AI Product Management with Udacity: Course Review & Insights

We don't usually write reviews for non-university sponsored courses, but we loved this one at Udacity so much we made an exemption! Udacity's Ai Product Management course is a masterclass in all things AI Product Management. We all know AI is super hot right now, so this nanodegree is designed to equip learners with the specialized skills required to succeed in managing AI products of all types. This comprehensive program focuses on practical applications of AI in business, from initial concept through to deployment and iteration.

The program features experienced instructors such as Alyssa Simpson-Rochwerger, Kirsten Gokay, Kiran Vajapey, and Meeta Dash, all of whom bring extensive industry knowledge and practical insights.

Best for: Beginners

This course is heavily focused on AI-beginners and starts with the basics of communicating with large-language models. The only prerequisites are basic computer skills, such as using a browser and accessing ChatGPT.

Program Features

• Estimated Time: Approximately 2 months with 5-10 hours of study per week.
• Support & Resources: Access to technical mentors, project reviews, a proprietary wiki (Knowledge), interactive workspaces, and auto-graded quizzes.
• Career Services: Personal career services including GitHub portfolio reviews, LinkedIn optimization, and personal brand establishment.

We recapped the learning objectives from each week to set your expectations for course material. The great part about this certification is that it's self-paced-- meaning that if you're super determined you can likely knock it out in a weekend. However, we've recapped the material in weekly chunks for you here. The primary focus of the entire cert is teaching the different types of engagements you can have while prompting the AI. Each week mostly focuses on the different themes-- we found this format to be incredibly helpful and thoughtful provoking.

Learning Objectives from Weeks 1-2: Introduction to AI in Business

• Overview: This course covers the fundamentals of AI and machine learning, focusing on how businesses can leverage these technologies to drive innovation and efficiency. Learners will understand when and how to apply AI to specific business cases and develop clear, data-driven strategies for AI product implementation.
• Sections:
  
  • Introduction to AI & Machine Learning:
    • Learn the basics of AI and machine learning, including key terminologies such as supervised learning, unsupervised learning, and neural networks.
    • Understand how businesses derive value from AI by automating repetitive and time-consuming tasks.
  • Using AI & ML in Business:
    • Learn to narrow down a business use case and decide when to use AI in a product.
    • Develop strategies for measuring the success of AI products.
    • Understand how to build and manage an AI product team that can handle data and test product efficacy over time
  • Project:
    • Create a business case for an AI application, defining clear metrics for success and outlining the necessary data and team requirement

Learning Objectives from Week 2-4: Create a Dataset

• Overview: High-quality data is crucial for successful AI models. This course teaches learners how to develop, annotate, and manage datasets that are relevant, complete, and unique. The course includes practical experience using data annotation platforms.
• Sections:
  • First Project:
    • Create an annotated training dataset on Appen’s platform for a medical imaging classification system to flag serious cases of pneumonia.
  • Data Fit & Annotation:
    • Learn to analyze the size and fit of data for specific product use cases.
    • Use Figure Eight’s crowdsourced data annotation platform to generate high-quality datasets with human annotation.
    • Design effective annotation instructions to ensure accurate data labeling.
  • Second Project: Medical Image Annotation:
    • Define a product goal for a medical diagnostic tool.
    • Design an annotation job for a medical image dataset, considering metrics for success and improvements.
    • Create test questions for annotators to ensure data quality.

Learning Objectives from Week 4-6: Build a Model

• Overview: This course focuses on building machine learning models, understanding neural networks, and evaluating model performance. Learners will gain hands-on experience with automated machine learning tools such as Google AutoML.
• Sections:
  • First Project:
    • Build, train, and evaluate models using Google AutoML, implementing and testing different data variants to optimize model performance.
  • Training & Evaluating a Model:
    • Learn how neural networks learn from training data.
    • Use test data to evaluate a trained model based on accuracy, precision, and recall metrics.
    • Understand transfer learning and how pre-trained models can be adapted to new use cases.
  • Second Project: Build a Model with Google AutoML:
    • Build and train a model using Google’s AutoML for a medical imaging use case.
    • Evaluate multiple models to determine the best one for the given product use case, understanding how data variations impact model performance.

Learning Objectives from Week 6-8: Measuring Impact & Updating Models

• Overview: Post-deployment, the value of AI models is measured by their business impact. This course covers techniques for assessing and improving model performance, managing bias, ensuring data security, and scaling AI products.

• Sections:
  • First Project:
    • Create a business proposal for an AI product, including detailed plans for development, deployment, and ongoing evaluation.
  • Measuring Business Impact & Mitigating Bias:
    • Learn how to measure the business outcomes of AI products using A/B testing and versioning.
    • Develop strategies to mitigate unwanted bias in machine learning models and ensure compliance with data security regulations.
    • Case Study: Video Annotation:
      • Follow an end-to-end AI product development cycle.
      • Learn to prototype solutions incrementally and continuously update models based on user feedback and performance metrics.
  • Second Project: THE CAPSTONE
    • Develop a comprehensive business proposal for an AI product of the learner’s choosing.
    • Define success metrics, scope the dataset, plan the model development, and create a post-deployment monitoring plan.

Udacity recently changed their billing structure, which could be a great thing if you're determined to do this quickly. It used to be a flat rate of around $2000 for the course, but now it's $249/month. You can get a slight discount if you pre-pay 4 months, but since this course is only 8 weeks or so, we don't recommend doing that! A healthy tip: they seem to be rather promotion heavy. I personally recommend downloading the syllabus and seeing if they send any discount codes your way.

If you have a learning budget at your current company, or are dedicated to upskilling your career into something analytics related– we recommend completing the certificate and getting the nanodegree documentation/certificate (GET RECEIPTS!). This will help make your Linkedin and resume more searchable to recruiters who may be looking for specific keywords and programs. To audit the program and simply learn the material, this program is completely free. Learn more about how to include MOOCs on your resume here.

This course is brand new, which is similar to the OpenAI's chat tool itself. However, the course averages a 4.9 star review with 100+ ratings so far. The ratings breakdown is 91% 5 Star, 8% 4 Star, and <1% 3 Star. No 1's or 2's to be found! We wanted to call out how many folks specifically mentioned their adoration for Dr. White-- almost all of the reviews mentioned how wonderful he is!

Aggregated Student Reviews for Udacity's AI Product Manager Nanodegree Program

Positive Reviews

1. Comprehensive and Practical Content:
   • Many students appreciate the balance between theoretical and practical aspects of the course. The program covers essential AI product management skills, including building models with Google AutoML and creating annotated datasets using platforms like Figure Eight. The hands-on projects are particularly praised for their real-world relevance and application​​​​.
2. Strong Support System:
   • The mentor support and detailed project reviews are highlighted as significant benefits. Students mention that mentors provide prompt and thorough feedback, which enhances the learning experience and helps in mastering the concepts​​​​.
3. Career Services:
   • Udacity's career services receive positive feedback for their professionalism and helpfulness. Students find the resume and LinkedIn optimization services beneficial for job placement and career advancement. The platform's focus on job-readiness, including GitHub portfolio reviews, is also appreciated​​​​.
4. Short, Engaging Lessons:
   • The structure of the lessons, which are concise and to the point, helps maintain student interest. This format is particularly appreciated for its effectiveness in delivering complex concepts without overwhelming learners​​.

Negative Reviews

1. High Cost:
   • The program is considered expensive, especially compared to other MOOCs offering similar content. Some students feel that the cost is not justified unless they can secure discounts or scholarships. The monthly payment plan can add up quickly if the course takes longer to complete​​​​.
2. Platform and Technical Issues:
   • There are complaints about having to create accounts on third-party platforms, which sometimes require credit card information. Additionally, some students have faced technical issues with the Figure Eight platform and found the instructions for certain projects confusing or insufficient​​​​.
3. Variable Instructor Quality:
   • While some instructors are praised for their clarity and engagement, others are noted to be less effective. Issues such as difficult-to-understand accents and inaccurate subtitles have been mentioned as hindrances to the learning experience​​.
4. Mismatch Between Course Content and Project Specifications:
   • Some students found discrepancies between the course content and the requirements of the projects. This mismatch necessitated additional research and time to complete the projects, which was not always clearly communicated during the lessons​​.

Notable Quotes

• Positive: "The mentor will read all your codes piece by piece, not only the result. This is the unique feature of Udacity."​​
• Negative: "The Google AutoML project has been fun and rewarding learning experience thus far. I look forward to re-taking the AI Programming using Python course after completing more Python courses on Coursera and finding more time in my schedule to confront other course challenges."​​

Overall, the Udacity AI Product Manager Nanodegree program is well-regarded for its practical approach and strong support system, though it comes with some challenges, particularly related to cost and technical issues. For those who can navigate these challenges, it offers valuable skills and career support.

This course from Vanderbilt is great as a showable certification and jumping-off point, but may not teach you everything you need to know to get a role in a tech-adjacent field. Here are some other fabulous programs in the AI space, with a focus on hard skills to compliment the general knowledge provided in this cert:

If you're looking to know AI & Product Management: Duke University's AI Product Management

Both Duke and UVA are incredibly prestigious organizations working to increase public knowledge of product management. This is a mid-level course-- so have some basic knowledge under your belt first-- focused on product management in the realm of artificial intelligence. Read our full writeup here. It's also free to audit, but if you want the certificate (recommended), it's $79 a month to complete at your own pace.

Note: there are tons of alternate courses on how to use ChatGPT effectively, especially on Udemy. We specifically are reviewing this one from Vanderbilt because it's a sharable certification from a renowned university.

Prompt-City: ChatGPT Prompt Engineering with 2100+ Prompts

This course ranges between $15-40, and is very useful for finding inspiring prompts. This is different from the Vanderbilt class in that it offers tons of copy-and-paste prompts for various questions, while the other teaches how to think about interacting with the AI. Could be a great enhancer if you're looking to get super familiar with the tool.

Highest Rated: ChatGPT Complete Guide: Learn Midjourney, ChatGPT 4 & More

This is the highest rated/top selling Udemy ChatGPT class, and for good reason. It covers all interactions with the tool, from thinking about prompt delivery to a 17-page prompt guide. We especially enjoyed the section for engineers around using ChatGPT to program, QA and debug. The course cost ranges between $15-70 depending on sale season.

The Udacity AI Product Manager Nanodegree program offers a comprehensive blend of theoretical knowledge and practical application, making it a valuable choice for those looking to enter or advance in the field of AI product management. The program's structured approach, including hands-on projects and real-world scenarios, equips learners with essential skills such as building AI models, managing data annotation, and measuring business impact.

Students have highlighted the strong support system, particularly the prompt and detailed feedback from mentors, as a significant advantage. Additionally, the career services provided by Udacity, including resume and LinkedIn optimization, are well-regarded for their contribution to job readiness and career advancement​​​​.

However, the program is not without its drawbacks. The high cost can be a barrier, and some students have faced technical issues and found certain instructor-led sessions challenging to follow due to language barriers and inaccuracies in subtitles. Despite these challenges, many find the program's unique projects and practical focus to be highly rewarding and applicable to real-world AI product management tasks​​​​.

In conclusion, while the Udacity AI Product Manager Nanodegree is a significant investment, it offers substantial benefits for those committed to advancing their careers in AI product management. By leveraging the program's comprehensive curriculum, strong mentor support, and career services, learners can develop the skills needed to succeed in this rapidly evolving field. Here at Bridged we are huge fans of stacking micro-certifications to achieve desired career results, which is why we created the skill tracker. We're still in beta and building a product to make your career planning fun and affordable. We'd love to talk to YOU! Was this article helpful? Did you enroll in the course?

Let us know at hello@getbridged.co