Program  

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Corporate
Our Students
Resources
Bootcamp Programs
Short Courses
Portfolio Courses
Bootcamp Programs

Launch your career in Data and AI through our bootcamp programs

  • Industry-leading curriculum
  • Real portfolio/industry projects
  • Career support program
  • Both Full-time & Part-time options.
Data Science & Big Data
Data Engineering

Become a data analyst through building hands-on data/business use cases

Become an AI/ML engineer by getting specialized in deep learning, computer vision, NLP, and MLOps

Become a DevOps Engineer by learning AWS, Docker, Kubernetes, IaaS, IaC (Terraform), and CI/CD

Short Courses

Improve your data & AI skills through self-paced and instructor-led courses

  • Industry-leading curriculum
  • Portfolio projects
  • Part-time flexible schedule
AI ENGINEERING
Portfolio Courses

Learn to build impressive data/AI portfolio projects that get you hired

  • Portfolio project workshops
  • Work on real industry data & AI project
  • Job readiness assessment
  • Career support & job referrals

Build data strategies and solve ML challenges for real clients

Help real clients build BI dashboard and tell data stories

Build end to end data pipelines in the cloud for real clients

Location

Choose to learn at your comfort home or at one of our campuses

Corporate Partners

We’ve partnered with many companies on corporate upskilling, branding events, talent acquisition, as well as consulting services.

AI/Data Transformations with our customized and proven curriculum

Do you need expert help on data strategies and project implementations? 

Hire Data, AI, and Engineering talents from WeCloudData

Our Students

Meet our amazing alumni working in the Data industry

Read our students’ stories on how WeCloudData have transformed their career

Resources

Check out our events and blog posts to learn and connect with like-minded professionals working in the industry

Read blogs and updates from our community and alumni

Explore different Data Science career paths and how to get started

Data Engineer Learning Path

The main reason why data engineering can be a separate position and not merged into software engineering is that data engineers need to understand data. A good data engineer not only needs to understand the knowledge of systems and development, but also needs to have a deep understanding of data. Therefore, to be a good data engineer, you need to have the ability of data and various system codes at the same time. To become a data engineer, you need to learn a few things.

Data: A Data Engineer is supposed to know data modeling very well, know how to transform a business requirement into schemas and tables in a database or data warehouse. In addition, data engineers must have good SQL ability, the difficulty of using SQL for a data engineer is higher than that for Data Analysts and BI. Therefore, if you want to become a data engineer, learning SQL well is a must. In addition, data engineers must be sensitive to data. When you see a form of raw data, you should be able to quickly spot the patterns and find some of the problems. This is very important, because data engineers build their data engineering work on the basis of these raw data. This is also a feature that distinguishes data engineers from software engineers.

Programming: Data engineers also need strong coding skills, after all, we are using code and programs to complete projects. So it is necessary to learn various programming languages. The most important of these are SQL and Python. The importance of SQL has been mentioned earlier, while Python plays the same import role in Data Engineering.In a Data Engineering project, Data Engineers use Python to do data extraction, data transformation, oading, etc. In many cases, data engineers use both SQL and Python at the same time. When designing big data, data engineers will use some spark packages, such as Pyspark, SparkSQL, etc. Of course, more advanced big data development will also use Scala, Java, etc.

Cloud services: The current projects are mainly on cloud services, such as Aws, AZURE, GCP. Therefore, a data engineer must be proficient in using some cloud services, such as AWS, EC2, S3, Lambda, EMR and so on.

Databases: Various databases exist in this industry, including relational and NoSQL databases. As a data engineer, you need to know how to use these databases, how to query, download, and upload data from these databases.

Of course, data engineers need to have more knowledge than mentioned here, such as software engineering ability, documentation ability, etc. But these are the basic skills you should have to become a data engineer.

Check out other career guides

Our Career Guide provides all the resources you will need to help you get started in navigating data careers. We include free resources, guides, and tools that will help you get started.

WeCloudData

WeCloudData is the leading data science and AI academy. Our blended learning courses have helped thousands of learners and many enterprises make successful leaps in their data journeys.

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