Spark, Hadoop, and Snowflake for Data Engineering from Coursera

e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programmingGain the skills for building efficient and scalable data pipelines. Explore essential data engineering platforms (Hadoop, Spark, and Snowflake) as well as learn how to optimize and manage them. Delve into Databricks, a powerful platform for executing data analytics and machine learning tasks, while honing your Python data science skills with PySpark. Finally, discover the key concepts of MLflow, an open-source platform for managing the end-to-end machine learning lifecycle, and learn how to integrate it with Databricks.

This course is designed for learners who want to pursue or advance their career in data science or data engineering, or for software developers or engineers who want to grow their data management skill set. In addition to the technologies you will learn, you will also gain methodologies to help you hone your project management and workflow skills for data engineering, including applying Kaizen, DevOps, and Data Ops methodologies and best practices.

With quizzes to test your knowledge throughout, this comprehensive course will help guide your learning journey to become a proficient data engineer, ready to tackle the challenges of today's data-driven world.

What's inside

Syllabus

Overview and Introduction to PySpark

This week, you will learn how to work with different data engineering platforms, such as Hadoop and Spark, and apply their concepts to real-world scenarios. First, you will explore the fundamentals of Hadoop to store and process big data. Next, you will delve into Spark concepts, distributed computing, deferred execution, and Spark SQL. By the end of the week, you will gain hands-on experience with PySpark DataFrames, DataFrame methods, and deferred execution strategies.

Snowflake

This week, you will explore the Snowflake platform, gaining insights into its architecture and key concepts. Through hands-on practice in the Snowflake Web UI, you'll learn to create tables, manage warehouses, and use the Snowflake Python Connector to interact with tables. By the end of this week, you'll solidify your understanding of Snowflake's architecture and practical applications, emerging with the ability to effectively navigate and leverage the platform for data management and analysis.

Azure Databricks and MLFLow

This week, you will practice the essential skills for seamlessly managing machine learning workflows using Databricks and MLFlow. First, you will create a Databricks workspace and configure a cluster, setting the stage for efficient data analysis. Next, you will load a sample dataset into the Databricks workspace using the power of PySpark, enabling data manipulation and exploration. Finally, you will install MLFlow either locally or within the Databricks environment, gaining the ability to orchestrate the entire machine learning lifecycle. By the end of this week, you will be able to craft, track, and manage machine learning experiments within Databricks, ensuring precision, reproducibility, and optimal decision-making throughout your data-driven journey.

DataOps and Operations Methodologies

This week, you will explore the concepts of Kaizen, DevOps, and DataOps and how these methodologies synergistically contribute to efficient and seamless data engineering workflows. Through practical examples, you will learn how Kaizen's continuous improvement philosophy, DevOps' collaborative practices, and DataOps' focus on data quality and integration converge to enhance the development, deployment, and management of data engineering platforms. By the end of this week, you will have the knowledge and perspective needed to optimize data engineering processes and deliver scalable, reliable, and high-quality solutions.

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Primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming

Teaches essential data engineering platforms (Hadoop, Spark, and Snowflake) and how to optimize and manage them

Develops Python data science skills with PySpark

Covers key concepts of MLflow, an open-source platform for managing the end-to-end machine learning lifecycle

Teaches methodologies to help hone project management and workflow skills for data engineering, including applying Kaizen, DevOps, and Data Ops methodologies and best practices

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Spark, Hadoop, and Snowflake for Data Engineering with these activities:

Seek Guidance from Experienced Spark Practitioners

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Connect with individuals who have expertise in Spark and data engineering to gain valuable insights and guidance.

Browse courses on Apache Spark

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Identify potential mentors through online platforms or networking events
Reach out to potential mentors and introduce yourself
Establish a mentorship relationship and schedule regular meetings

Read 'Learning Spark: Lightning-Fast Big Data Analysis'

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Gain a comprehensive understanding of Spark's architecture, programming model, and key concepts through a well-regarded book.

View Learning Spark: Lightning-Fast Big Data Analysis on Amazon

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Purchase or borrow the book
Read the book, taking notes and highlighting important concepts
Complete the exercises and examples provided in the book

Participate in Spark Study Group

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Engage with peers, share knowledge, and work collaboratively on Spark-related projects or assignments.

Browse courses on Apache Spark

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Find or create a study group with peers
Establish regular meeting times and topics
Participate in discussions, code reviews, and project collaborations

Five other activities

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Work Through Spark Tutorial

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Gain practical experience working with Spark, a powerful tool for distributed data processing and efficient handling of large-scale datasets.

Browse courses on Apache Spark

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Access Spark Tutorial
Follow provided instructions
Complete tutorial and exercises

Attend Spark Machine Learning Workshop

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Expand your knowledge of Spark's machine learning capabilities by attending a hands-on workshop.

Browse courses on Big Data Analytics

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Search for upcoming Spark machine learning workshops
Register for the workshop and prepare
Attend the workshop and engage in activities

Solve Spark Coding Challenges

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Sharpen your Spark coding skills by solving a series of challenges that test your understanding of Spark's capabilities and syntax.

Browse courses on Apache Spark

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Find Spark coding challenges online
Select a challenge and read the problem statement
Code the solution using Spark
Test and debug your code
Submit your solution

Build a Data Pipeline with PySpark

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Apply your understanding of PySpark and data engineering principles by designing and implementing a real-world data pipeline.

Browse courses on Data Engineering

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Define the data sources and their formats
Create a PySpark program to read, transform, and write data
Deploy your pipeline on a cluster or cloud platform
Monitor and maintain your pipeline

Contribute to Open-Source Spark Projects

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Gain practical experience, contribute to the Spark community, and deepen your understanding of Spark's underlying implementation.

Browse courses on Apache Spark

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Identify open-source Spark projects on platforms like GitHub
Review project documentation and identify areas to contribute
Fork the project and make your modifications
Submit a pull request with your proposed changes

Career center

Learners who complete Spark, Hadoop, and Snowflake for Data Engineering will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers design, build, and maintain data pipelines. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Engineer.

See salaries and explore the career path for Data Engineer

Data Architect

Data Architects design, build, and maintain data systems. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Architect.

See salaries and explore the career path for Data Architect

Machine Learning Engineer

Machine Learning Engineers design, build, and maintain machine learning models. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Big Data Architect

Big Data Architects design, build, and maintain big data systems. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Big Data Architect.

See salaries and explore the career path for Big Data Architect

Data Scientist

Data Scientists use data to build models that can predict future outcomes. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Scientist.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use data to identify trends and patterns, and to develop insights that can help businesses make better decisions. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Analyst.

See salaries and explore the career path for Data Analyst

Data Quality Analyst

Data Quality Analysts are responsible for the assessment and improvement of data quality. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Quality Analyst.

See salaries and explore the career path for Data Quality Analyst

Business Analyst

Business Analysts use data to identify problems and opportunities, and to develop solutions that can help businesses achieve their goals. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Business Analyst.

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Data Governance Analyst

Data Governance Analysts are responsible for the development and implementation of data governance policies and procedures. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Data Governance Analyst.

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Cloud Architect

Cloud Architects design, build, and maintain cloud-based applications. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Cloud Architect.

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Product Manager

Product Managers are responsible for the development and management of products. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Product Manager.

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Database Administrator

Database Administrators are responsible for the installation, configuration, and maintenance of databases. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Database Administrator.

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Project Manager

Project Managers are responsible for the planning, execution, and management of projects. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Project Manager.

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Systems Administrator

Systems Administrators are responsible for the installation, configuration, and maintenance of computer systems. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Systems Administrator.

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Software Developer

Software Developers design, build, and maintain software applications. The skills you will learn in this course, including working with Hadoop, Spark, and Snowflake, as well as optimizing and managing them, will be essential for success in this role. By taking this course, you will gain the knowledge and experience needed to excel as a Software Developer.

See salaries and explore the career path for Software Developer