Harvard University · edX
Introduction to Data Science with Python
4.3174 ratingsLearn the concepts and techniques that make up the foundation of data science and machine learning.
Overview
This specialization features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the specialization.
This specialization prepares you to become an AWS data engineer by teaching you to build data pipelines, process large datasets, and manage workflows using key AWS services. You’ll start with core data engineering concepts, then dive into AWS Glue for ETL and Amazon Redshift for data warehousing. Learn streaming with Kinesis and MSK, big data processing on EMR, and scalable data lakes with Lake Formation. You’ll query data using Athena, visualize insights in QuickSight, and orchestrate pipelines with Step Functions and AppFlow. Migration tools like DMS, DataSync, and Snow Family are also covered. Designed for data professionals and cloud engineers with basic AWS and data knowledge, this hands-on program is ideal for intermediate learners.
By the end of the specialization, you will be able to design, build, and optimize scalable data pipelines, implement real-time analytics, manage large-scale data migrations, and deploy end-to-end data engineering workflows on AWS.
Courses in this learning path or series 3
- Introduction to Data Engineering on AWS
- Advanced Data Processing and Analytics with AWS
- Orchestrating Data Pipelines and Advanced Data Strategies
Advantages and disadvantages
Advantages
- Structured courses with graded quizzes, assignments and deadlines you can reset.
- A shareable certificate from the university or company when you pay.
- Financial aid is often approved for students in India (apply 15 days before you need it).
- Covers niche tools that universities don't teach.
- Self-paced: start any time.
- A clear syllabus (3 parts) you can see before you start.
Disadvantages
- Paid after a 7-day free trial (Coursera Plus or per course).
- Some courses can be audited for free, but graded work and certificates need payment.
- Many courses are produced quickly from slides and screen recordings; read the reviews first.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
- Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
- Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
Packt is in Tier 5: mass-produced or unclear of our institution ranking (40/100). Thousands of courses turned out quickly; check reviews first.
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