Data Science with Scala

Data Science with Scala

Public courses

£1950

- Anyone can join the training
- Course outline as presented on the website
- Small groups, 3-10 people

Private courses

Price set individually

- Training workshop just for your team
- You choose date and location of the training
- Course outline tailored to your needs

About the training

Data Science with Scala is one of  the two trainings of Scala for Data Scientists series. Full of great examples with interesting sets of data it provides one with the necessary information and skills for every data scientist. The training concerns topics connected with acquiring, storing, manipulating, processing and visualizing data in Scala.

The training aims at providing Data Scientists with the knowledge which is essential in creating scalable architecture needed for processing and modeling data. The practical approach of trainers enables the participants of the training to acquire a number of useful skills and increase their productivity in Data Science branch.

Who is this training for?

  • Data Scientist
  • Data Engineer
  • Java Programmer

What will I learn?

  • Import data from flat files and web API
  • Design scalable architecture for Data Science
  • Program applications utilizing parallel computing
  • Put together Scala with Akka and Apache Spark
  • Create interactive visualizations

Course outline

  1. Introduction to Data Science with Scala
    • Data Science
    • Programming languages and tools for Data Science
    • Installation and configuration of Scala
    • Application of Scala in Data Science
    • References
  2. Data Manipulation with Breeze
    • Introduction to Breeze
    • Breeze data types
    • Documentation and getting help
    • Basic data operations
    • Alternative libraries
    • Examples of data manipulation
  3. Interacting with Scala and SQL through JDBC
    • First steps with JDBC
    • Functional wrappers
    • Data access layer
  4. Interfacing SQL with Slick
    • Column operators
    • Group by operations
    • Accessing metadata
    • Slick vs JDBC
  5. Web API interface
    • Web API
    • JSON in  Scala
    • Concurrency
    • Authentication
  6. Web API with Play
    • Client-Server apps
    • Web frameworks
    • Building an application
    • Play framework
    • Actions
  7. Scala with MongoDB
    • MongoDB
    • Connecting with MongoDB
    • Accessing objects in database
    • Complex queries
    • Serialization
  8. Concurrency with Akka
    • Introduction to Akka
    • Actor construction
    • Routing
  9. Distributed processing with Spark
    • Configuring Spark
    • Resilient distributed datasets
    • Building and running programs
    • Data partitioning
  10. Spark SQL and Dataframes
    • Aggregation
    • Operations on Dataframes
    • SQL queries on Dataframes
    • Complex data types
  11. Machine learning with Spark ML
    • Introduction to ML
    • Pipeline components
    • Evaluation
    • Common machine learning algorithms in Spark
    • Cross validation and model selection
  12. Data visualization with breeze viz
    • Drawing plots
    • Formatting
    • Advanced plots
    • Alternative methods for data visualization

Course Curriculum

Curriculum is empty

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