Udacity Data Engineer Nanodegree Review
Data is all over the place, and knowing how to use and process it comes with a world of endless possibilities. Data Engineers act as creators of complex blueprints that process this information in a systematic way. While the jumble of numbers may look intimidating to just any ordinary person, to the Data Engineer, this means magic, where their carefully constructed pipeline mimicking code can pump out easy to read graphs and visuals.
This skillset is crucial in the technology and data driven world we live in today, where companies with collected data can use these visuals to make financial and business minded predictions to brighten their future. This is a position that can prove useful across all markets, especially as each of them make their digital conversions.
Gaining the knowledge necessary to aid companies in their digital transition is now easier than ever, especially with help from online courses and all-inclusive academies like Udacity. In this review, we will take a look at the course from start to finish plus, see if the price and timing make it worth it for you. We’ll also finish with a peek in to the job market, with a glance at the possibilities of landing a job after successful completion.
Udacity attempts to break the molds of online certification courses, offering a wide range of both free introductory and in-depth nanodegree courses. Their initial goal was to bring topics of computer sciences to all learners that were anxious to dive in, beginning with only a few free courses. Now, they create full nanodegrees, some in collaboration with big names in the industry to produce knowledgeable graduates.
The Udacity Data Engineer certificate program is a nanodegree, one that comes combined with several Udacity extras. Each nanodegree has a set of perks to go along with the course which include:
You’ll be in full control of the amount of time your take to complete the course. This means that you can log in as often as you like day or night on any day of the week.
Learners will not only receive some assistance when it comes to creating the perfect resume, they also get to have a mock interview with a member of career services. These guys will then give useful feedback that can be taken along for the real deal.
Real Industry Projects
To try and prepare learners the best way possible, the projects that are sewn throughout the course are designed to closely mirror real industry problems. These normally require that learners combine all the knowledge learned from the beginning to the end. This course in particular, as well as a few others, comes with a capstone project at the end.
On top of everything else, you’re paired with a mentor that is there to help if problems arise. Not only technological problems but, problems keeping up with the workload or wrapping your head around some of the more complex topics.
Another thing that stands out about the academy is the instructors, carefully selected to include those with experience both in the field and instructing. The video-based topics are led by the following instructors:
As a developer for DataStax, she chose to keep her focus on bridging the gap between customer and engineering. Before that, she was a software engineer for different sets of databases helping to create workflows that process data efficiently.
A massive amount of broad range experience is what comes with Ben. He has worked with a ton of complicated processes, including Computer Visions and Natural Language Processing. Currently, he is employed with SuperHero, where he single-handedly built their team of A-list engineers.
His focus has been more on the security side of data. He’s been a lecturer on cybersecurity and distributed systems, which led him to his current position as the CEO of Novelari.
On the structural side of things, Olli enjoys the building and managing of pipelines, creating flows that process large loads of data. Apart from passing on his knowledge as an instructor, he is an active data engineer with Wolt.
Before we dig into the course, let’s first take a look at what you will need before you sign up. This is considered to be an intermediate course, one that requires a basis of some sort in a few of the topics. The suggested knowledge includes:
- Experience with Python
- Work with and knowledge about:
- Strings, numbers and variables
- Lists and dictionaries
- Troubleshooting and debugging
- Algorithms and data structures
- Experience with SQL including:
- Joins and aggregations
- Definition and manipulation of tables
If this sounds like a bit much for the foundation and knowledge that you have, you can take a walk over to the many introductory courses to either brush up or begin building a knowledge base. You can find the introductory courses both free and at a cost here: https://www.udacity.com/courses/all
Alright, so now on to the course. It is broken up into five sections, each of which come with checkpoints at each topic introduced. Almost every section comes with a project which requires that you apply the knowledge learned. We have dissected each of the sections below, giving you a look into what you’ll be learning throughout each one.
You’ll begin with a look at data consumers seeing what it takes to meet the needs through relational NoSQL models. As a way to work with the knowledge learned in the lectures, you’ll get to do some of your own data modeling using two different platforms: Postgres and Apache Cassandra.
Cloud Data Warehouse
In this part of the course, you’ll be working with Amazon Web Services (AWS), a highly useful platform for building. You’ll learn about unique data infrastructures, creating cloud-based warehouses. At the end, you’ll actually build a warehouse for data, getting to apply the techniques you just learned.
Spark and Data Lakes
Spark is a useful tool for large quantities of data. This section is all about Spark and how it can be used to build data lakes. You’ll actually finish this section having constructed your own data lake.
Data Pipeline with Airflow
Apache Airflow is another software on the list that you’ll be using when creating pipelines that filter and process data. You’ll build a pipeline in this part, seeing how to automate and monitor the flow of data from start to finish.
The course will end with your very own capstone project. You will choose the type of project you’d like to create, including researching and collecting data which you will then organize and summarize. This project is diverse enough to be included on your portfolio which you can send along with your resume to land your first gig.
After looking at all that you’ll be working with, you’re probably wondering how long it will all take. Udacity estimates that the entire course can be completed in 5 months if you dedicate 10 to 15 hours a week. As we mentioned above, you’ll actually have all the time you need and want but, this could be both an advantage and disadvantage.
It’s a plus because you’re never rushed and can take your time, not having to feel pressured to be on time at any time. On the other hand, taking too long could leave gaps in between useful knowledge and projects which call for its application. Also, the price is equally correlated to the time it takes, increasing the longer you take.
Udacity Data Engineer Nanodegree Cost:
After that last line we may have left you wondering what the cost has to do with the time. Udacity charges for the course per monthly access, giving you a few different options that you can choose from to pay. These options include a per month payment where the cost is $359. This will allow you to have access for as long as you want as long as you pay the price. As you may be able to tell, the total cost could go pretty high if you let it, so for those on a budget you should beware.
The other option comes with an offer from the academy that has to do with the estimated time the entire course is said to take. This price comes with a lower monthly cost of $206 per month but, you do have to pay the entire 5 months up front. You’re getting a good deal here, especially if you think it will take you the full 5 months.
Currently, there is a deal going on, one where the academy is giving away a free month. This comes with either option, where you can score a free month with the bundle or with the per month price. Either way, this makes the deal even sweeter, especially when bundling up. You’ll get a total of 5-month access for the price of 4 plus a discounted price.
To add some perspective, we thought we’d include reviews from the students that have already taken the course. Overall, the course has received a rating of 4.5 stars out of a total 5, so what learners had to say was mainly positive. Here is what a few had to say:
“I just finished the first project, and everything has been great so far. I didn’t pass the project on my first submission, but the feedback helped me pass on my second submission. I’ve worked with PostgreSQL before. So, the first section was somewhat familiar. I’m excited continue the program and learn more about NoSQL and larger scale tools on AWS.” (5-stars)
“Program is OK. I think concepts are still fairly basic. The exercises are also very easy. I wish it was more challenging and more depth was covered onto the benefits of Postgres, limitations, how it scales, etc. Perhaps those will be covered in later sections. The project was challenging enough. I think there was still a bit too much handholding with much of the code being templated for us. Rather, I think it could be offered as hints in a separate doc so we can try from scratch and only if we’re stuck for a while, use a hint to help overcome an obstacle.” (3-stars)
Data Engineer Job Market:
An article published by Dice claimed that Data Engineers were in one of the top positions for the most in demand jobs out there. They claim that there is actually a shortage in the field, with a need of nearly 200,000 data scientists. Another report done by DataNami.com claims that the market is said to jump up 50%. As of 2019, the average salary listed was around $160,000 per year. As far as starting salary, the average falls around $100,000. Basically, to sum this all up, the demand seems to be here to stay and this job title is not one that will be leaving any time soon.
Taking all things into account, it should be pretty simple to see why the academy continues to get solid ratings. The curriculum is well-rounded and takes learners from the foundations to a broader range of skills that can help graduates break into the field confidently. A team of dynamic instructors in the industry that come from top-tier companies is also a huge plus, not to mention the extras included in each nanodegree program.
Now is surely one of the best times to jump in and get certified, especially thanks to the current discount up and running. If you have thought about a career as a data engineer, now is a great time to get on board, as the market is nowhere near its peak. The faster you begin the quicker your skills will evolve, leading you up the ladder to bigger and better opportunities and bigger and better pay.