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Data engineering is a crucial aspect of the data science and analytics domain, focusing on the design, construction, and maintenance of data pipelines, databases, and data warehouses.
In this blog, we will explore some excellent courses tailored for beginners who aspire to learn the fundamentals of data engineering and kickstart their career in this exciting field.
Level: Beginner
Duration: Approx 2 months (10 hours/week)
Fee: Free to audit, upgrade for certificates and financial aid also available
What you’ll learn: Data Engineering Ecosystem and Lifecycle, Python Programming Basics, Relational Database fundamentals and working with MySQL, PostgreSQL & IBM Db2, SQL
About the course: This Specialization consists of 5 self-paced online courses that encompass the essential skills needed for data engineering, covering topics such as the data engineering ecosystem and lifecycle, Python, SQL, and Relational Databases.
By engaging with instructional videos and hands-on exercises using authentic tools and real-world databases, you will acquire these fundamental data engineering prerequisites. As a result, individuals will develop a comprehensive understanding of data engineering, attain practical skills applicable to a data-oriented profession, and lay the groundwork for a successful data engineering career.
Here is a snapshot of 5 courses in this specialization:
Upon the successful completion of these courses, participants will possess the practical knowledge and experience necessary to delve further into the field of data engineering and tackle more advanced data engineering projects.
Link to the courses: Here.
Level: Beginner
Duration: 5 Months (10 hours/week)
Fee: Free to audit, upgrade for certificates and financial aid also available
What you’ll learn: Data Science, ETL & Data Pipelines, Relational Database Management Systems (RDBMS), NoSQL and Big Data, Python Programming, Data Analysis, Database (DBMS), Apache Spark, SQL
About the course: This professional certification consists of 13 courses that will teach you data engineering from scratch and if you want a career in Data engineering then this program will teach you the foundational data engineering skills employers are seeking for entry level data engineering roles, including Python, one of the most widely used programming languages. You’ll also master SQL, RDBMS, ETL, Data Warehousing, NoSQL, Big Data, and Spark with hands-on labs and projects.
You’ll learn to use Python programming language and Linux/UNIX shell scripts to extract, transform and load (ETL) data. You’ll also work with Relational Databases (RDBMS) and query data using SQL statements and use NoSQL databases as well as unstructured data.
When you complete the full program, you’ll have a portfolio of projects and a Professional Certificate from IBM to showcase your expertise. You’ll also earn an IBM Digital badge and will gain access to career resources to help you in your job search, including mock interviews and resume support.
Link to the courses: Here.
Level: Intermediate
Duration: Approx 30-35 hours
Fee: Free, no certificates
What you’ll learn: Azure, Azure Synapse, Apache spark pools, work with Data warehouses using azure synapse, transfer and transform data using azure synapse analytics pipelines, work with Azure Data bricks
About the course: Microsoft provides one of the best free learning materials about Data science and AI. This Data engineer career path consists of 9 courses and prepares you for Azure Data Engineer Associate Certifications exam DP-203. These courses have modules that will help you build skills and advance your career in Data Engineering.
The Data Engineer Career Path is designed to help you learn how to design and implement the management, monitoring, security, and privacy of data using the latest technologies and tools. You can find more information about this career path on the Microsoft Learn website.
Link to the course: Here.
Level: Beginner
Duration: Approx 43 min
Fee: Free
What you’ll learn: understanding Big Data
About the course: This short course is for those who are curious to know what Big Data is all about. If you are looking to understand how Big Data impact large and small business then this course is for you.
The course covers the following topics:
1. Unraveling Big Data problems through easy-to-understand examples.
2. Tracing the origins and evolution of Hadoop, from its early days before it was even called "Hadoop."
3. Discovering the magic of Hadoop that makes it uniquely powerful.
4. Clarifying the distinction between Data Science and Data Engineering, a common source of confusion when choosing a career path or understanding job roles.
5. Demystifying Hadoop vendors like Cloudera, MapR, and Hortonworks by learning more about them.
By the end of the course, you'll have a solid foundation in tackling Big Data challenges and utilizing Hadoop to address them effectively.
Link to the course: Here.
Level: Beginner
Duration: 4 weeks (9-10 hours/week)
Fee: Free
What you’ll learn: Hadoop, HDFS, Hive, and Spark, ETL, ELT, and Data Pipelines, Data Warehouses, Data Marts, and Data Lakes, RDBMS, NoSQL, Data Wrangling and querying etc.
About the course: This course is designed to introduce you to the fundamental concepts of data engineering, its ecosystem, lifecycle, processes, and essential tools. The Data Engineering Ecosystem comprises various components like data repositories, integration platforms, data pipelines, languages, and BI/reporting tools. Data pipelines acquire data from diverse sources, while repositories store and process it. Integration platforms create a unified view for secure access by data consumers who use BI and analytical tools for valuable insights.
Through practical labs, you'll provision a data store on IBM Cloud, load data, and gain hands-on experience in data processing.
Link to the course: Here.
These carefully curated programs offer a comprehensive understanding of essential concepts, tools, and technologies required in the data engineering ecosystem. From mastering programming languages like Python and SQL to exploring data warehouses, ETL processes, and big data technologies, these courses will equip you with the knowledge and practical skills needed to succeed as a data engineer.
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