Data Science at Scale using Spark and Hadoop Training in Germany

  • Learn via: Classroom / Virtual Classroom / Online
  • Duration: 3 Days
  • Price: Please contact for booking options
We can host this training at your preferred location. Contact us!

Data scientists build information platforms to provide deep insight and answer previously unimaginable questions. Spark and Hadoop are transforming how data scientists work by allowing interactive and iterative data analysis at scale.

Learn how Spark and Hadoop enable data scientists to help companies reduce costs, increase profits, improve products, retain customers, and identify new opportunities.

Cloudera University’s three-day course helps participants understand what data scientists do, the problems they solve, and the tools and techniques they use. Through in-class simulations, participants apply data science methods to real-world challenges in different industries and, ultimately, prepare for data scientist roles in the field.

There are no prerequisites for this course.

This course is suitable for developers, data analysts, and statisticians with basic knowledge  of Apache Hadoop: HDFS, MapReduce, Hadoop Streaming, and Apache Hive as well as experience working in Linux environments. Students should have proficiency in a scripting language; Python is strongly preferred, but familiarity with Perl or Ruby is sufficient

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, and develop concrete skills such as:

  • How to identify potential business use cases where data science can provide impactful results
  • How to obtain, clean and combine disparate data sources to create a coherent picture for analysis
  • What statistical methods to leverage for data exploration that will provide critical insight into your data
  • Where and when to leverage Hadoop streaming and Apache Spark for data science pipelines
  • What machine learning technique to use for a particular data science project
  • How to implement and manage recommenders using Spark’s MLlib, and how to set up and evaluate data experiments
  • What are the pitfalls of deploying new analytics projects to production, at scale

Introduction

  • About This Course
  • About Cloudera
  • Course Logistics
  • Introductions

Data Science Overview

  • What Is Data Science?
  • The Growing Need for Data Science
  • The Role of a Data Scientist

Use Cases

  • Finance
  • Retail
  • Advertising
  • Defense and Intelligence
  • Telecommunications and Utilities
  • Healthcare and Pharmaceuticals

Project Lifecycle

  • Steps in the Project Lifecycle
  • Lab Scenario Explanation

Data Acquisition

  • Where to Source Data
  • Acquisition Techniques

Evaluating Input Data

  • Data Formats
  • Data Quantity
  • Data Quality

Data Transformation

  • File Format Conversion
  • Joining Data Sets
  • Anonymization

Data Analysis and Statistical Methods

  • Relationship Between Statistics and Probability
  • Descriptive Statistics
  • Inferential Statistics
  • Vectors and Matrices

Fundamentals of Machine Learning

  • Overview
  • The Three C’s of Machine Learning
  • Importance of Data and Algorithms
  • Spotlight: Naive Bayes Classifiers

Recommender Overview

  • What is a Recommender System?
  • Types of Collaborative Filtering
  • Limitations of Recommender Systems
  • Fundamental Concepts

Introduction to Apache Spark and MLlib

  • What is Apache Spark?
  • Comparison to MapReduce
  • Fundamentals of Apache Spark
  • Spark’s MLlib Package

Implementing Recommenders with MLlib

  • Overview of ALS Method for

Latent Factor Recommenders

  • Hyperparameters for ALS Recommenders
  • Building a Recommender in MLlib
  • Tuning Hyperparameters
  • Weighting

Experimentation and Evaluation

  • Designing Effective Experiments
  • Conducting an Effective Experiment
  • User Interfaces for Recommenders

Production Deployment and Beyond

  • Deploying to Production
  • Tips and Techniques for Working at Scale
  • Summarizing and Visualizing Results
  • Considerations for Improvement
  • Next Steps for Recommenders

Conclusion



Contact us for more detail about our trainings and for all other enquiries!

Upcoming Trainings

Join our public courses in our Germany facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom
23 Mai 2024
Berlin, Hamburg, Münih
3 Days
Classroom / Virtual Classroom
08 Juli 2024
Berlin, Hamburg, Münih
3 Days
Classroom / Virtual Classroom
06 Juli 2024
Berlin, Hamburg, Münih
3 Days
Classroom / Virtual Classroom
10 Juli 2024
Berlin, Hamburg, Münih
3 Days
Classroom / Virtual Classroom
08 Juli 2024
Berlin, Hamburg, Münih
3 Days
Classroom / Virtual Classroom
17 Juli 2024
Berlin, Hamburg, Münih
3 Days
Classroom / Virtual Classroom
18 August 2024
Berlin, Hamburg, Münih
3 Days
Classroom / Virtual Classroom
19 August 2024
Berlin, Hamburg, Münih
3 Days
Data Science at Scale using Spark and Hadoop Training Course in Germany

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.


Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

Another popular city is Munich, which is famous for its Oktoberfest beer festival that attracts millions of visitors every year. Munich is also home to many historic buildings, including Nymphenburg Palace and the Marienplatz town square.

The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.
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