Land yourself a Data Engineer job upon completion of these free courses and certifications

Can one be a data engineer for free? I can bet my life on yes, and here’s the proof in terms of 10 free data engineering courses.

The Value of Free Education
People say that whenever one buys a commodity, he should look out for value for money. But the best value for money is getting a good thing for free. But are there such things? Supposedly not, if we go by the saying, “No such thing as a free lunch”.

I say there is such a thing as a free lunch, and I’m about to prove it! I dug out 10 educational ‘free lunches’ – free data engineering courses that also provide quality knowledge. Yes, it is true; there’s much more variety and choice if you can or want to pay tens, hundreds, sometimes even thousands of dollars.

Courses like these are widely termed ‘free’ by many other free course lists. For some, $90 one-off or $45/month is free. In reality, however, many people do not have that money to spend on a ‘free’ course, even though they are very willing to learn data engineering—also, let’s get real! Free literally means, well, free! Not ‘cheap’, not ‘very little money’, or ‘affordable’. Free!

What I researched, really, is that these courses are free. Many come from edX. In case you decide to have free access to the course, you need to complete it in a certain time—usually six months. But that should be enough to complete every course quite comfortably. Also, note that free access means you don’t get lifetime access to all the materials; they are deleted once you finish, and no certificate. Despite this, you should be able to use the courses to learn data engineering.

Before I talk about the courses, let’s briefly overview the role of a data engineer. That way, knowing what to look for in courses will be easier.

Understanding the Role of a Data Engineer

Data engineers make the data available—existential availability—to data team members and other stakeholders. On their part, they wrangle data and construct/maintain Data infrastructure, such as ETL processes, data pipelines, data storage.

Essential Skills of Data Engineers

Of course, the courses should cover all or some of those skills. Let’s take a closer look at the courses – pun intended – which will comprise your educational free lunch.

Free Data Engineering/Data Analytics Courses

1. Deep Learning with TensorFlow

Category: Machine Learning

Learn to apply deep learning techniques using TensorFlow for handling unlabeled and unstructured data like images, sound, and text.

What You Will Learn:

• TensorFlow Basics: Core concepts, functions, and operations.
• Neural Network Implementation: Tasks like regression, classification, and error minimization.
• Deep Learning Techniques: Backpropagation, CNNs, RNNs, and autoencoders.
• Unsupervised Learning: Applications and models like Restricted Boltzmann Machines and Deep Belief Networks.

Course Modules

1. Introduction to TensorFlow: Basics, regression models, and activation functions.
2. Convolutional Neural Networks (CNN): History, understanding, and applications.
3. Recurrent Neural Networks (RNN): Introduction, LSTM, and practical models.
4. Unsupervised Learning: Applications and collaborative filtering.
5. Autoencoders: Introduction, applications, and deep belief networks.

2. Data Engineering by ASU
Enroll at edX for free
Duration: 5 Months at 1-11 hours/week; learn at your own pace
What you will learn:

This is an introductory course by Arizona State University, dealing with

–Perform basic business analytics operations in Excel: Including data aggregation with PivotTable and distribution analysis through statistics and visualizations.
–Become familiar with database structures: The star schema and other data joining techniques.-
Process data by writing report queries: Building complex scripts and leveraging SQL for database analysis.
–Visualize data with Tableau: Creating interactive dashboards that can integrate multiple visualizations for business decision-making.
–Construct a predictive model in Python without needing a statistics prerequisite, gaining knowledge on different algorithms used for complex business analysis insights.

3. Python and Pandas for Data Engineering by Pragmatic AI Labs
Enroll at edX for free
Duration: 4 weeks at 3-6 hours/week; learn at your own pace
What You Will Learn:
Python environment setup and package management
Core Python syntax and data structures
Pandas DataFrames for data manipulation
Alternatives to Pandas for big data
Development with Vim, VS Code, and Git

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