Professional Certificate in Data Engineering
Online
DURATION
6 Months
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
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EARLIEST START DATE
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TUITION FEES
USD 7,450
STUDY FORMAT
Distance learning
Scholarships
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Introduction
Build a Career in Data Engineering With In-Demand Skills
As data grows even more integral to business, it’s easy to see why data engineering was ranked as the fastest-growing tech occupation in 2020. The need for data engineers who can build out the infrastructure necessary to put data to work is intensifying, and the MIT xPRO Professional Certificate in Data Engineering can help you meet this demand with job-ready data engineering skills that offer a competitive edge in the marketplace.
- $136,188 The average annual salary of a data engineer in the US in 2022 (Source: Indeed)
- 95% The estimated proportion of digital transformation projects accounted for by cloud-native platforms by 2025, up from 40% in 2021 (Source: Gartner)
"Data engineering really is a core component of today’s data infrastructure. And because organizations can’t function without data, it’s also a career with a great deal of opportunity and incredibly interesting work as well."
– Abel Sanchez, Research Scientist and Executive Director of MIT’s Geospatial Data Center
Ideal Students
Who Is This Program For?
- Career Launchers: Recent STEM graduates/post-graduates/interns looking to start a career in this high-growth field by gaining exposure to data engineering
- Career Builders: Early career software engineers/technology professionals seeking to train in the latest data engineering tools and techniques and advance their careers
- Career Switchers: Mid-career professionals aiming to switch to data engineering from IT, analytics, finance, project management, supply chain, or another technical field
Applicants must have:
- A bachelor's degree or higher
- Strong math skills
- Some programming experience
Also recommended:
- An educational background in STEM fields
- Technical work experience
- Some experience with Python, R, or SQL
- Some experience with statistics and calculus
Program Outcome
Key Takeaways
- This program is designed to give you the skills you need to start or continue your career in data engineering. High-level learning outcomes for this program include:
- Develop and analyze databases using data science and data engineering tools and skills, including SQL and Python
- Configure a network to ensure data security
- Implement artificial intelligence (AI)/machine learning (ML) algorithms, including those for reinforcement learning and deep neural networks
- Manage big data using data warehousing and workflow management platforms
- Build a user interface to view and interact with large amounts of live-streaming data
- Create a GitHub portfolio to present the projects that you create to potential employers
Program Highlights
- Earn a certificate and 36 Continuing Education Units (CEUs) from MIT xPRO
- Insights and coding demos from renowned MIT faculty
- Learn market-ready data engineering skills in a high-growth market
- Build a GitHub portfolio of your projects to share with potential employers
- Receive one-on-one career support from Emeritus and introductions to hiring partners for eligible participants
Curriculum
Program Topics
- Introduction to Python
- Python: Introduction to NumPy
- Python: pandas
- Databases: SQL
- Databases: Basic SQL Statements
- Database Analysis and the Client–Server Interface
- A Model to Predict Housing Prices
- ETL, Analysis, and Visualization
- GitHub and Advanced Python Functions
- Software Engineering Basics
- Basics of Client–Server Architecture
- Types of Databases and Database Containerization
- CDC
- Java and Debezium
- Using Advanced Python Programming to Create Web Applications
- Transit Data and Application Programming Interfaces (AFIs)
- Performing ETL Using NiFi
- Platforms for Handling Big Data
- Processing Big Data with Spark and Airflow
- Introduction to ML and Advanced Probability
- Introduction to Reinforcement Learning and Deep Neural Networks
- Processing and Streaming Big Data
- Creating a Data Pipeline
- Handling Big Data with Mosquitto, ThingsBoard, and Kafka
Career Opportunities
Stepping into a career in data engineering requires a variety of skills, both hard and soft. This course offers you guidance for navigating a career path into tech, including crafting your materials and acing an interview. These services are provided by Emeritus, our learning collaborator for this program. The program support team includes course leaders to help you reach your learning goals. The primary objective is to give you the skills needed to be prepared for a job in this field. Eligible participants may receive introductions to our hiring partners; however, job placement is not guaranteed.
Elements of the career preparation aspects of this course include:
- Crafting your elevator pitch
- Optimizing your LinkedIn profile
- Writing resumes/cover letters
- Navigating your job search
- Learning interview tips and preparation
- Negotiating salary
Career exercises focused on launching a career as a data engineer include:
- Building your personal brand and promoting your skills
- Communicating technical concepts to non-technical colleagues
- Understanding the roles and workflow of Agile development
- Reflecting on your skills to discover how to troubleshoot and learn more quickly
- Job search and interviewing for data engineering positions