A data engineer is someone who is responsible for designing, implementing, and maintaining data systems. They work on a variety of projects from small to large companies and have a wide range of skills and experience. In today’s world, data engineering jobs are constantly growing in demand because of the ever-changing technology landscape.
A data engineer is a technical specialist who helps organizations manage and analyze data. They work on a wide range of projects from design to implementation and may be responsible for the collection, analysis, presentation, interpretation, or storage of data. A data engineer can also be involved in the creation of software that helps manage and analyze data.
In this Nanodegree program, Learn to provide a well-designed data model, develop databases, become proficient at designing data pipelines, and function with massive datasets. Upon the conclusion of the course, you will master the art of applying these techniques by the end of the capstone project.
Udacity is an educational organization providing a huge library of open online courses. It was founded by Sebastian Thrun, David Stavens, and Mike Sokolsky. Udacity was started with free computer science classes in 2011 through Stanford University. At Udacity, they provide various kinds of courses such as free courses and courses that come with online certifications such as Nanodegree Programs.
Some of the unique features you will find at Udacity cannot be found anywhere else. These unique features are what actually make Udacity one of the very best platforms by which you can enroll in an online course.
- Real-world projects from top industry experts
With real-world projects and engaging content created in collaboration with top-tier firms, you’ll master the IT skills that employers demand.
- Technical Support by mentors at Udacity
The Smart and knowledgeable mentors at Udacity will guide your learning and are always available to answer your questions, help you and keep you on track
- Career services
You’ll have access to GitHub portfolio reviews and LinkedIn profile optimization to help you develop your career and obtain a high-paying position.
- Learn with your own freedom
Create a learning plan that matches your busy schedule. Learn at your own speed and on your own timetable to achieve your specific goals.
Class content – Content Co-created with Insight, Real-world projects, Project reviews, and Project feedback from experienced reviewers
Student services – Technical mentor support, Student Community
Career services – Github review, Linkedin profile optimization
Meet Your Instructors
- Amanda Moran – Developer Advocate at DataStax
- Ben Goldberg – Staff Engineer at SpotHero
- Sameh El-Ansary – CEO at Novelari & Assistant Professor at Nile University
- Olli Iivonen – Data Engineer at Wolt
- David Drummond – VP of Engineering at Insight
- Judit Lantos – Data Engineer at Split
- Juno Lee – Instructor
To reach success in this program, you ought to be intermediate in completing Python programs and SQL queries. Intermediate Python programming knowledge, of the sort gained through the Programming for Data Science Nanodegree program, programs, or another introductory programming course, can be confirmed through additional real-world software development experience.
Now let’s come to the most important part of the course which is the course itself and what you get in it when you enroll in this course. This Course has a total of five sections each explaining some important topics related to the course and providing with you learning points and real-world projects at the end. Let’s take a deep dive into the sections -:
In this section, You will understand how to design relational data models to suit the needs of data consumers. Use ETL to create a database in PostgreSQL and Apache Cassandra.
In this project, you will be focusing on modeling user activity data for a music streaming app called Sparkify. You will learn how to create a relational database and assemble an ETL pipeline to simplify querying based on what songs users are listening to. You’ll also use PostgreSQL to define Fact and Dimension tables and populate the tables with new information.
In the second project, you will model user activity data for a music streaming service called Sparkify. You will create a NoSQL database and ETL pipeline designed to efficiently handle inquiries regarding which songs users are currently listening to. You will model your data in Apache Cassandra to provide for exhibiting specific queries that may be given by the researchers at Sparkify.
Cloud Data Warehouses
In this section, Improve your data warehousing capabilities and develop greater comprehension of data infrastructure. Create a cloud-based data warehouse on Amazon Web Services (AWS).
For this project, you must build an ETL pipeline that extracts the data from S3, stages them in Redshift, and transforms them into a set of dimensional tables for the analytics team to continue to develop insights into what songs their users listen to.
Spark and Data Lakes
In this section, Understand the big data ecosystem and be able to use Spark to analyze massive datasets. Store big data in a data lake and peruse it through Spark.
In this project, you’ll be tasked with building the ETL pipeline for the lake of data you’ve amassed. Your data is located in S3, in a directory of JSON logs on user activity on the program, as well as a directory containing JSON metadata of the songs in the program. You will load data from S3, process this data into tables using Spark, and then load the results back into S3. You’ll be tasked with deploying this Spark process on a cluster using AWS.
Data Pipelines with Airflow
In this section, Schedule, automate, and monitor data pipelines by using Apache Airflow. Perform data quality checks, trace data lineage, and work with data pipelines in the production process.
In this project, you’ll continue to build a music streaming platform’s data processing infrastructure by automating and creating a set of pipelines. You’ll configure and monitor pipelines with Airflow and debug production pipelines.
In this section, Show what you’ve learned about data science should be put together to develop a new data engineering workshop project.
The main goal of your data engineering capstone project is to apply your data science knowledge to a real-world problem. You’ll specify the scope of the project and what data you’ll be working on. You’ll gather data from different data sources to manipulate, interrelate, and summarize it; and create a clean database for others to analyze.
According to the Program, the course is expected to be completed within approximately 5 months if you devote a minimum of 5-10 hours per week to the course. As we mentioned above, they have a self-paced learning environment, so you can attend at your discretion and at your pace.
If you take more than 5 months to finish the course, you have to take the monthly pay-as-you-go plan and pay extra which will increase your overall cost of the course.
Now let’s talk about the cost of the course which is an important part of whether you will buy or not buy the course. In this course, Either you will pay for monthly access or you can also choose a 5-Months access plan.
If you choose the monthly pay-as-you-go option you will pay $399 per month and there is another option that you can choose which comes with exclusive discounts which is a 5 months plan that you need to pay upfront and costs you around $1695 which comes with exclusive discounts making it cheaper than the monthly plan and also recommended by Udacity.
If you pay upfront for the 5 months’ access you can save up to 15% + 70% exclusive discounts which you cannot if you take the monthly plan. If you need more time after 5 months, you can switch to a monthly access plan but it will increase the overall cost of the course.
Udacity will give you personalized Discounts if you answer 2 questions and pay upfront rather than a pay-as-you-go plan. You will get a promo code with a 70% Discount on your course by just answering 2 simple questions.
While looking at ratings and reviews of this course, One has to say that this course is very popular among the students with an overall rating of 4.5 out of 5 stars, and many good quality reviews are given by already enrolled students in the courses. Some of the reviews are -:
“Fantastic. Great experience thus far, having finished the first class. While I think there may be some difficulties for a computer novice – having to establish a node env for earlier node versions is a bit more of an advanced skill, IMHO – for where my knowledge level in programming is, even having zero knowledge of blockchain, the pace and content is perfect for your intermediate software engineer.
And I can’t say enough good things about the project review process. The feedback I received was so warmly welcomed and helpful in really understanding how to code better.”– Mark K.
“The content is interesting so far and I’ve learnt a good amount. The 1st project code review for done promptly and thoroughly. FYI prospective candidate – these requests for course reviews are done after the 1st of 4 projects, so I don’t know what the Ethereum content is like. However, the Bitcoin content is out of date, including interviews with CEOs of now defunct projects.
You need to use NVM to use an old version of Node, but this is not explained anywhere, so you have to work it out yourself. Also the version of Bitcoin Core mentioned is from 2018. So Udacity if you’re reading this – please keep your content more up to date.”-Anthony S.
As the industry has evolved, so too has the demand for data engineers. A recent study by Gartner predicts that the number of data engineers will grow from 50,000 in 2020 to 200,000 in 2022. This growth is due to various reasons – including the increasing use of artificial intelligence and machine learning; the growing complexity and diversity of data; and the need for better skills in engineering, business, and marketing. According to IBM, the median salary for a data engineer is $75,000.
This is overall a good course created by experts at Udacity and also the features and offers provided by Udacity make this course a very good Nanodegree program. Also, You should also check other courses which you can take right after this course as those courses are made with help of top tech companies, they are of high quality and make you more knowledgeable about your field. If you are interested in other Udacity courses, please check out all courses on our website.
The course also has easy to follow a curriculum that includes everything to build your foundation. And also every section at the end includes a real-world project that will give you practical experience and make you job-ready.
One thing you should keep an eye on is your timing, try to complete your course in the estimated time provided by the course, or else you have to pay more for extra months which will increase your overall cost of the course.
If you think that the Udacity Data Engineer Nanodegree Course is right for you, Udacity is the perfect place for you to take the course and land your dream job.