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Julien Richard-Foy

In the final capstone project you will apply the skills you learned by building a large data-intensive application using real-world data.

You will implement a complete application processing several gigabytes of data. This application will show interactive visualizations of the evolution of temperatures over time all over the world.

The development of such an application will involve:

— transforming data provided by weather stations into meaningful information like, for instance, the average temperature of each point of the globe over the last ten years ;

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In the final capstone project you will apply the skills you learned by building a large data-intensive application using real-world data.

You will implement a complete application processing several gigabytes of data. This application will show interactive visualizations of the evolution of temperatures over time all over the world.

The development of such an application will involve:

— transforming data provided by weather stations into meaningful information like, for instance, the average temperature of each point of the globe over the last ten years ;

— then, making images from this information by using spatial and linear interpolation techniques ;

— finally, implementing how the user interface will react to users’ actions.

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What's inside

Syllabus

Project overview
Get an overview of the project and all the information to get started. Transform data provided by weather stations into meaningful information.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Covers real-world data-intensive application development, a highly relevant industry skill
Led by instructors recognized for their expertise in data science
Includes hands-on labs and interactive materials, enhancing practical learning
Builds a strong foundation in data manipulation and visualization techniques
Involves transforming raw data into meaningful insights, a valuable skill in various fields
Students should have prior experience with data analysis tools and techniques

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Reviews summary

Functional scala data capstone project

According to learners, this Capstone project is a highly challenging but ultimately rewarding culmination of the Functional Programming in Scala specialization. Students appreciate the opportunity to apply their skills to a large, real-world data processing application. While the project provides invaluable practical experience, many note a significant difficulty jump from previous courses and point out that instructions can be vague, often requiring extensive self-exploration. Some also mention facing setup and infrastructure issues. Overall, it's seen as a rigorous test that consolidates knowledge for those prepared for the challenge.
Requires solid knowledge from prior courses.
"You definitely need to have a solid understanding from the preceding courses."
"Be comfortable with Scala and functional concepts before attempting this capstone."
"Prior knowledge from the specialization is absolutely essential to succeed."
Apply skills to a large, realistic problem.
"I loved building a real-world application involving data processing and visualization."
"Applying functional programming concepts to a large project like this was incredibly valuable."
"The hands-on experience with big data in a functional style is a major strength."
Some users reported issues with setup.
"Getting the project environment set up took more time than I expected."
"I ran into problems with the provided infrastructure and spent a lot of time troubleshooting."
Guidance can be vague, requiring self-study.
"Instructions can sometimes be vague, which means you have to figure things out yourself."
"Debugging was tough because the guidance wasn't always clear enough."
"I felt like I needed more hints and clearer examples to make progress."
Project is very difficult and demanding.
"This project is very challenging; be prepared to spend a lot of time on it."
"The difficulty is a big jump from the earlier courses in the specialization."
"It's way too hard if you don't have a strong background."

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 Functional Programming in Scala Capstone with these activities:
Machine Learning Resource Compilation
Organize and compile helpful resources related to machine learning to support your learning journey.
Show steps
  • Search for online articles, tutorials, books, and videos on machine learning algorithms, techniques, and applications.
  • Categorize and organize the resources based on topics and difficulty levels.
  • Create a resource document or online repository for easy reference.
Linear Algebra I
Revisit the basics of linear algebra to strengthen your foundation for this course.
Browse courses on Matrix Operations
Show steps
  • Review notes and past assignments from a previous linear algebra course.
  • Complete online tutorials or practice problems on matrix operations.
  • Solve systems of linear equations using Gaussian elimination.
Project Discussion Group
Collaborate with peers to brainstorm ideas, share progress, and provide constructive feedback on your capstone project.
Browse courses on Capstone Project
Show steps
  • Join a group of 3-5 students who are also working on the capstone project.
  • Meet regularly to discuss your project ideas and progress.
  • Provide feedback and suggestions to improve each other's projects.
Three other activities
Expand to see all activities and additional details
Show all six activities
Exploratory Data Analysis Report
Conduct an in-depth analysis of a real-world dataset to gain insights and prepare for the capstone project.
Browse courses on Exploratory Data Analysis
Show steps
  • Select a dataset and gather necessary information.
  • Explore and visualize the data using techniques like histograms, scatterplots, and box plots.
  • Perform statistical analysis to identify patterns and relationships.
  • Write a report summarizing your findings and insights.
Machine Learning Hackathon
Participate in a hackathon to apply your skills, collaborate with peers, and enhance your understanding of machine learning concepts.
Show steps
  • Team up with fellow students and choose a machine learning challenge.
  • Develop a machine learning model and evaluate its performance.
  • Present your findings to a panel of experts and receive feedback.
Kaggle Machine Learning Competition
Challenge yourself and showcase your skills by participating in a Kaggle machine learning competition.
Browse courses on Kaggle Competitions
Show steps
  • Choose a competition that aligns with your interests and skill level.
  • Develop a machine learning model and submit your predictions.
  • Analyze your results, identify areas for improvement, and refine your approach.

Career center

Learners who complete Functional Programming in Scala Capstone will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers apply their expertise in data modeling, data integration, data quality, and data security to design and construct data pipelines that transform raw data into usable, consistent formats. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Software Engineer
Software Engineers design, develop, test, deploy, and maintain software systems. Functional Programming in Scala Capstone may be useful as this course covers how to implement a complete application processing several gigabytes of data, making images from this information, and more.
Web Developer
Web Developers design and develop websites and web applications. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, making images from this information, and more.
Statistician
Statisticians collect, analyze, interpret, and present data to help make informed decisions. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Quantitative Analyst
Quantitative Analysts (Quants) use mathematical and statistical models to analyze financial data and make investment decisions. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve complex problems. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Business Analyst
Business Analysts analyze business processes to identify areas for improvement. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Database Administrator
Database Administrators manage and maintain databases to ensure data integrity and performance. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
Information Architect
Information Architects design and implement information systems to meet the needs of users. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, using various interpolation techniques, and more.
User Experience (UX) Designer
User Experience (UX) Designers create user interfaces and experiences that are intuitive and enjoyable. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, making images from this information, and more.
Graphic designer
Graphic Designers create visual concepts and images to communicate messages. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, making images from this information, and more.
Cartographer
Cartographers create maps and charts to represent geographical data. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, use spatial and linear interpolation techniques, and more.
Geospatial Analyst
Geospatial Analysts use geospatial data and technologies to solve problems and make decisions. Functional Programming in Scala Capstone may be useful as this course covers how to transform data provided by weather stations into meaningful information, use spatial and linear interpolation techniques, and more.

Reading list

We've selected 12 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 Functional Programming in Scala Capstone.
Provides a comprehensive overview of functional programming in Scala, covering the basics of functional programming, as well as more advanced topics such as monads and type classes. It valuable reference for anyone interested in learning more about functional programming in Scala.
Provides a comprehensive introduction to functional and reactive domain modeling, covering topics such as domain-driven design, event sourcing, and CQRS.
Provides a concise and practical introduction to Scala, covering the basics of the language and how to use it for real-world applications.
Provides a comprehensive introduction to Scala for machine learning, covering topics such as data manipulation, feature engineering, and model building.
Collection of recipes for solving common problems in Scala. It covers a wide range of topics, from basic programming tasks to more advanced topics such as concurrency and functional programming. It valuable resource for anyone who wants to learn more about Scala.
Provides a hands-on introduction to data analytics with Scala and Spark, covering topics such as data exploration, machine learning, and streaming analytics.
Provides a deep dive into the internals of Apache Spark, the distributed computing framework used in the course for big data processing.
Provides a practical guide to using Scala for big data analytics, covering topics such as data ingestion, transformation, and visualization.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data cleaning, transformation, and visualization.
Provides a comprehensive introduction to R for data science, covering topics such as data manipulation, modeling, and visualization.
Provides a collection of recipes for common problems in Scala, covering topics such as data structures, functional programming, and concurrency.
Provides a deep dive into the Scala language, covering topics such as type system, concurrency, and functional programming.

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