Udacity Data Product Manager Nanodegree Review [Is It Worth It?]

Are you planning to enroll in Udacity Data Product Manager Nanodegree?… If yes, first, you must read this Udacity Data Product Manager Nanodegree Review.

In this review, I have shared everything you need to know regarding the Udacity Data Product Manager Nanodegree Program such as the content and project quality, the positives and drawbacks of the Nanodegree program, and how you can save some money while enrolling in the program.

Now, without further ado, let’s get started-

Udacity Data Product Manager Nanodegree Review

Let’s start with the Udacity Data Product Manager Nanodegree Course Content and Projects-

How are the Udacity Data Product Manager Nanodegree Content and Projects?

The best thing I found in this Udacity Data Product Manager Nanodegree Program was the balance between theory and projects. I enrolled in various related courses on data product manager, but most courses covered only theory. But this Nanodegree Program was unique and that’s why it is expensive as compared to other courses.

Now, let’s see what I have learned during this Udacity Data Product Manager Nanodegree.

In this Nanodegree program, there were 3 Courses and 3 projects. After every course, there was one project, which I had to finish before moving to the next course. This approach helped me to clear my theoretical doubts.

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Course 1- Applying Data Science to Product Management

Being a data science enthusiast, this course was interesting to me. In this first course, I learned the concept of data product management, different types of data product managers, and the fundamentals of general product management from talking to customers, analyzing data, designing high-level solutions, prioritizing work, setting a roadmap, facilitating development, organizing launch communications, and producing product iterations.

Next, the instructor explained the benefits of aggregates or roll-up tables, compared and contrasted the differences between fact and dimensional tables, implemented enriching datasets, and utilize common online repositories for publicly available datasets for analysis.

In this course, I also learned how to use SQL and other data analysis techniques to explore and enrich a dataset to identify customer pain points, trends, and opportunities, how to interpret data and insights to come up with product objectives, how to drive instrumentation strategies for proper event data collection, how to assemble and arrange your narrative based on stakeholders and how to develop the key points to hit in a product proposal presentation.

After this course, there was one project which I had to finish and the project was-

Project 1- Develop a Data-Backed Product Proposal

In this project, I had to work as a data product manager for Flyber, the first flying taxi service provider in New York City. For this project, I had to acquire taxi data for a comparable initial analysis. This dataset had real taxi drop-offs and pick-ups in New York City.

My first step was to analyze the existing use cases for and identify temporal, behavioral, and spatial trends of ground-based taxis from the dataset. Next, I had to deep-dive into user research data to understand the general sentiment, desire, concerns, and use cases of flying cab service to prospective customers.

And at the end, I had to synthesize my insights to create a data-backed product proposal that recommends what features the first flying taxi service should have to maximize consumer delight, adoption, and profits.

I really enjoyed this project. When I completed this project, the reviewer reviewed my project and gave feedback. The feedback and the peer community helped me throughout the program to clear my doubts. After submitting this project, I moved to the next course.

Course 2- Establishing Data Infrastructure

In the second course, I learned about data pipelines such as their importance, various components, how to organize data pipeline components, how to create conceptual data pipelines, and the classic data problems that can be addressed by data pipelines.

Next, I understood data consumers such as primary data consumers and their data needs, components in building a relational data model, and how to apply relational data models to business scenarios.

The instructors also taught about data producers and data strategies. They explained how to create event data models and implement them to get business insights, how to use data collected from event models to calculate product KPIs, how to identify primary data producers in an organization, the difference between ETL and ELT processes, how to distinguish between batch processing and stream processing, and the data security and compliance (PII, PCI, HIPAA, GDPR, and CCPA) components related to product use cases.

Check 60% off Discount-> Udacity Data Product Manager Nanodegree

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After this course, there was another project, which I had to complete-

Project 2- Build a Scalable Data Strategy

In this project, again I had to act as a data product manager for Flyber. First, I defined the data needs of primary business stakeholders within the organization and create a data model to ensure the data collected supports those needs.

Next, I performed the necessary extraction and transformation of the data to make the data relevant to answer business
questions.

And at the end, I interpreted data visualizations to understand the scale of Flyber’s data growth and chose an appropriate data warehouse to enable that growth.

Throughout the project, you can clear your doubts with the mentor. They will guide you and review your project code.

Visit-> Udacity Data Product Manager Nanodegree

Course 3- Leveraging Data in Iterative Product Design

This was the last course of the Udacity Data Product Manager Nanodegree Program. In this course, I learned how data collection and usage change depending on the state of the software, how to choose common KPIs for different business models, how to identify the steps in a typical user acquisition and activation funnel, and how to visualize a funnel analysis in Tableau in bar chart form.

After that, the instructor taught the importance of segmenting user data by cohorts, how to apply cohort analysis to segment funnel analysis, the benefits and drawbacks of quantitative data, the framework of “jobs to be done” as used during qualitative research, the benefits and drawbacks of A/B testing, the benefits and drawbacks of multivariate testing, etc.

After this course, there was a last project of this Nanodegree program-

Project 3- Create an Iterative Design Path

For this project, first, I evaluated data from a conducted A/B test to identify key behavioral and descriptive attributes of users to define user personas and map out the significant stages of the user journey within the Flyber app.

Next, I created an assumption map to explain the testable risks, opportunities, and correlated KPIs for product design improvements of the app experience, including the most impactful page and the most significant subset of users.

And at the end, I used the completed assumption map as well as the developed user persona and journey to construct hypotheses for new product features of the Flyber app and experiments to validate these hypotheses.

Udacity provides technical mentor support. You can ask the mentor throughout the project whenever you have a doubt.

Check 60% off Discount-> Udacity Data Product Manager Nanodegree

[Use the code BACK2SKILLS]

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So, this is all about the course details and projects. The best thing I found about the Udacity Data Product Manager Nanodegree is that they focus on the Practical Aspects as well as the Theoretical part of Data Product Management.

The mentor will read all your codes piece by piece, not only the result. This is the unique feature of Udacity.

So, in terms of Content Quality, the Udacity Data Product Manager Nanodegree Program was worth it. I learned several new concepts. The mentor was available for answering questions almost instantaneously.

Now, the next parameter you must know is its Pricing. That means whether it is worth the money or not.

So, let’s see the price and duration of the Udacity Data Product Manager Nanodegree.

How Much Time and Money do You Have to Spend in the Udacity Data Product Manager Nanodegree?

According to Udacity, the Udacity Data Product Manager Nanodegree will take 3 months to complete if you spend 10 hours per week. And for 3 months they cost around $705.

But Udacity offers two options- One is either pay the complete amount upfront or you can pay monthly installments of $300/month.

I know the Udacity Data Product Manager Nanodegree is expensive compared to other MOOCs. At this price, I would say this is not worth it. Because you can learn these topics separately from other MOOCs.

But if you get the Udacity Data Product Manager Nanodegree at a low cost by applying for some discount or Scholarship, then you can go for it.

How to get a Discount on Udacity Data Product Manager Nanodegree?

Most of the time, Udacity offers some discounts. When they offer a discount, it appears something like that-

Visit the Nanodegree Page.

As you can see Udacity is offering a “Personalized Discount”.

So, you click on the “Personalized Discount” option. And you will be redirected to the next page where Udacity will ask you to answer two questions.

Answer these questions from the drop-down list. And you will get a 70% off on Udacity Data Product Manager Nanodegree.

They will provide a unique coupon code. You have to copy this code and paste it at the time of payment. And that’s all, you have to do to get a discount.

Check 60% off Discount-> Udacity Data Product Manager Nanodegree

[Use the code BACK2SKILLS]

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Now, the next most important point you must clear before enrolling in Udacity Data Product Manager Nanodegree is the Prerequisites.

Who Should Enroll in Udacity Data Product Manager Nanodegree?

This Nanodegree Program is best for those who have a basic understanding of data terminology (i.e. big data, database, algorithms, etc.) and some experience with data analysis (basic SQL and Tableau).

When you enroll in the Nanodegree Program, you will get elective courses too. And in these elective courses, you can learn these topics. But it’s better to have previous knowledge of these concepts.

Without having knowledge of these concepts, I would not suggest this Udacity Data Product Manager Nanodegree.

Now, let’s see how are the instructors of this Nanodegree Program-

Are Instructors Experienced?

• JJ Miclat– JJ is a product leader obsessed with creating simple, novel solutions for the world’s most challenging issues.
• Vaishali Agarwal– Vaishali is a Product Manager at Expedia.
• Anne Rynearson– Anne has 6+ years of experience in product management in the software industry, including EdTech and market research industries.

As you saw, all instructors are experienced and knowledgeable. And learning from such instructors is amazing and helpful. That is the reason I love Udacity.

Now, after covering all essential points related to Udacity Data Product Manager Nanodegree, it’s time to answer the-

Is Udacity Data Product Manager Nanodegree Worth It?

Yes, Udacity Data Product Manager Nanodegree is worth it because it has a perfect balance between theory and projects. Their technical mentor support feature was very helpful. You can clear your doubt with the mentor. This feature makes Udacity Data Product Manager Nanodegree unique. Along with that, You will get practical exposure by working on a Flyber project.

Check 60% off Discount-> Udacity Data Product Manager Nanodegree

[Use the code BACK2SKILLS]

Check Discount

Now it’s time to wrap up this Udacity Data Product Manager Nanodegree Review.

Conclusion

I hope this Udacity Data Product Manager Nanodegree helped you to decide whether to enroll in this program or not.

If you found this Udacity Data Product Manager Nanodegree helpful, you can share it with others. And if you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

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Thank YOU!

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