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Paweł Kordek

Learn how to work with very large datasets without leaving familiar and rich Python data ecosystem. This course will teach you how to leverage power of Dask library in order to handle data that is too big for regular tools like Pandas or NumPy.

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Learn how to work with very large datasets without leaving familiar and rich Python data ecosystem. This course will teach you how to leverage power of Dask library in order to handle data that is too big for regular tools like Pandas or NumPy.

Working with so-called ‘Big Data’ can be a daunting task and many tools that solve this problem have a very steep learning curve. Also, developers familiar with Python may not want to resort to solutions built on another technology stack. In this course, Scaling Python Data Applications with Dask 1, you will gain the ability to work with very large datasets using a Python-native and approachable tool. First, you will learn how to use Dask when your application written using standard Python stops working because of the growing size of the data. Next, you will discover how Dask works underneath and what techniques it uses to make processing large datasets in various scenarios possible and accessible. Finally, you will explore how to exchange Pandas and NumPy for their Big Data variants, with practically no changes to the code. When you’re finished with this course, you will have the skills and knowledge of Dask needed to confidently write data applications that scale, using exclusively Python stack.

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What's inside

Syllabus

Course Overview
Understanding Dask
Scaling Simple Python Data Apps
Dask Internals and Dashboard
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Scaling NumPy and Pandas
Beyond Single Machine

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches learners how to use Python libraries to work with Big Data, which is becoming increasingly important across industries
Employs industry-standard Python tools, so learners can seamlessly integrate their new skills into their existing workflows
Provides hands-on experience through the Dask library, giving learners practical skills they can apply immediately
Assumes learners have a foundation in Python, so those new to the language may need to catch up before enrolling

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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 Scaling Python Data Applications with Dask 1 with these activities:
Review Python Data Structures and Algorithms
Refresh your understanding of Python data structures and algorithms to strengthen your foundation for working with large datasets.
Browse courses on Data Types
Show steps
  • Write unit tests to verify your implementations
  • Review popular Python data structures and their applications
  • Implement common sorting and searching algorithms in Python
Review Python Programming Principles
This course requires a basic understanding of programming principles to ensure a solid foundation.
Browse courses on Python Programming
Show steps
  • Review basic data structures like lists, tuples, and dictionaries.
  • Practice writing simple functions and classes.
Walkthrough Dask Tutorial
Follow a guided tutorial on Dask to become familiar with its core concepts and functionalities.
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  • Set up your Dask environment
  • Create a Dask DataFrame and perform basic operations
  • Explore Dask's parallel computing capabilities
Five other activities
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Show all eight activities
Develop a Dask-based Data Processing Pipeline
Create a data processing pipeline using Dask to gain hands-on experience in handling large datasets effectively.
Show steps
  • Design a data processing workflow
  • Implement the pipeline using Dask
  • Optimize and evaluate the performance of your pipeline
Solve Dask Coding Challenges
Sharpen your Dask skills and problem-solving abilities by working through coding challenges specifically designed for Dask.
Show steps
  • Find online Dask coding challenges
  • Attempt to solve the challenges using Dask
  • Review your solutions and learn from your mistakes
Join a Dask Study Group or Online Community
Engage with other Dask learners to exchange knowledge, ask questions, and enhance your understanding.
Show steps
  • Find a Dask study group or online community
  • Introduce yourself and ask questions
  • Participate in discussions and share your knowledge
Build a Data Visualization Dashboard with Dask
Create an interactive data visualization dashboard using Dask to gain hands-on experience in presenting large datasets visually.
Show steps
  • Design the dashboard and identify relevant data
  • Use Dask to process and transform the data
  • Build the dashboard using Plotly or other visualization libraries
Become a Mentor for Beginner Dask Users
Deepen your understanding of Dask by mentoring others and reinforcing your own knowledge through teaching.
Show steps
  • Identify opportunities to mentor others
  • Prepare materials and resources
  • Guide and support beginner Dask users

Career center

Learners who complete Scaling Python Data Applications with Dask 1 will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers design, build, and maintain systems to manage and process data. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course will provide you with the skills and knowledge needed to become a successful Data Engineer. You will learn how to use Dask to scale your Python data applications and work with very large datasets. This course will also teach you how to use Dask Internals and Dashboard, and how to scale NumPy and Pandas.
Data Scientist
Data Scientists use data to solve real-world problems. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course will provide you with the skills and knowledge needed to become a successful Data Scientist. You will learn how to use Dask to scale your Python data applications and work with very large datasets. This course will also teach you how to use Dask Internals and Dashboard, and how to scale NumPy and Pandas.
Software Engineer
Software Engineers design, build, and maintain software applications. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course will provide you with the skills and knowledge needed to become a successful Software Engineer. You will learn how to use Dask to scale your Python data applications and work with very large datasets. This course will also teach you how to use Dask Internals and Dashboard, and how to scale NumPy and Pandas.
Database Administrator
Database Administrators manage and maintain databases. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course will provide you with the skills and knowledge needed to become a successful Database Administrator. You will learn how to use Dask to scale your Python data applications and work with very large datasets. This course will also teach you how to use Dask Internals and Dashboard, and how to scale NumPy and Pandas.
Data Analyst
Data Analysts use data to identify trends and patterns. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course will provide you with the skills and knowledge needed to become a successful Data Analyst. You will learn how to use Dask to scale your Python data applications and work with very large datasets. This course will also teach you how to use Dask Internals and Dashboard, and how to scale NumPy and Pandas.
Business Intelligence Analyst
Business Intelligence Analysts use data to improve business decisions. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course will provide you with the skills and knowledge needed to become a successful Business Intelligence Analyst. You will learn how to use Dask to scale your Python data applications and work with very large datasets. This course will also teach you how to use Dask Internals and Dashboard, and how to scale NumPy and Pandas.
Statistician
Statisticians use data to solve problems and make informed decisions. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Statistician. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Machine Learning Engineer. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Financial Analyst
Financial Analysts use data to make investment decisions. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Financial Analyst. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Operations Research Analyst
Operations Research Analysts use data to improve business operations. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Operations Research Analyst. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Actuary
Actuaries use data to assess risk and uncertainty. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Actuary. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Quantitative Analyst
Quantitative Analysts use data to make investment decisions. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Quantitative Analyst. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Data Visualization Analyst
Data Visualization Analysts use data to create visual representations of data. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Data Visualization Analyst. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Risk Analyst
Risk Analysts use data to assess risk and uncertainty. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Risk Analyst. You will learn how to use Dask to scale your Python data applications and work with very large datasets.
Auditor
Auditors use data to assess the financial health of organizations. They work with large datasets and use tools like Dask to handle the volume and complexity of data. This course may help you develop the skills and knowledge needed to become a successful Auditor. You will learn how to use Dask to scale your Python data applications and work with very large datasets.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Scaling Python Data Applications with Dask 1.
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This comprehensive guide provides a detailed overview of Dask's architecture, components, and usage. It serves as a valuable reference for understanding the underlying concepts and best practices for working with Dask.
Offers a comprehensive overview of data science principles and techniques using Python. It covers topics such as data exploration, machine learning, and deep learning, providing a valuable resource for those interested in the broader field of data science.
Explores concurrency and parallelism in Python. It covers topics such as threads, processes, and asynchronous programming, providing a valuable resource for understanding the concepts behind parallel computing in Dask.
Offers a practical guide to data analytics using Python. It covers essential concepts, such as data wrangling, data exploration, and machine learning, providing a foundation for working with large datasets.
This textbook provides a comprehensive overview of distributed and cloud computing concepts. It covers topics such as cloud architectures, distributed algorithms, and resource management, providing a foundation for understanding the underlying principles of Dask.
This textbook offers a comprehensive overview of high-performance computing principles and techniques. It covers topics such as parallel architectures, performance analysis, and cluster computing, providing a solid foundation for understanding the broader context of Dask.
This widely-used textbook introduces the fundamentals of data analysis using Python. It covers topics such as data structures, data manipulation, and data visualization, providing a strong foundation for working with large datasets.

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