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Working with Apache Kafka
Course Description Learn to use Kafka as your real-time data …
What you'll learn
Overview of Streaming technologies
Kafka concepts and architecture
Programming using Kafka API
Kafka Streams
Monitoring Kafka
Tuning/Troubleshooting Kafka
Hadoop Developer Foundations
Course Description New – Learn about the Hadoop ecosystem and …
What you'll learn
Introduction to Hadoop
HDFS
YARN
Data Ingestion
HBase
Oozie
Working with Hive
Hive advanced
Hive in Cloudera/Hortonworks Distribution (or tools of choice)
Working with Spark
Spark Basics
Spark Shell
RDDs
Spark Dataframes and Datasets
Spark SQL
Spark API programming
Spark and Hadoop
Machine Learning (ML/MLlib)
GraphX
Spark Streaming
Introduction to Apache Spark Essentials (TTSK7502)
Course Description Learn the essentials of using Spark for your …
What you'll learn
The essentials of Spark architecture and applications
How to execute Spark Programs
How to create and manipulate both RDDs (Resilient Distributed Datasets) and UDFs (Unified Data Frames)
How Spark core components come together for complete applications
Introduction to Hadoop Administration (TTDS6503)
Course Description Learn how to install, maintain, monitor, troubleshoot, optimize, …
What you'll learn
Understand the benefits of distributed computing
Understand the Hadoop architecture (including HDFS and MapReduce)
Define administrator participation in Big Data projects
Plan, implement, and maintain Hadoop clusters
Deploy and maintain additional Big Data tools (Pig, Hive, Flume, etc.)
Plan, deploy and maintain HBase on a Hadoop cluster
Monitor and maintain hundreds of servers
Pinpoint performance bottlenecks and fix them
Big Data Fundamentals
Learn the benefits of big data and the underlying technologies, …
What you'll learn
Navigate the technology stacks and tools used to work with big data
Establish a common vocabulary on your teams for applying big data practices
Get an overview of how big data technologies work: Apache Hadoop, Spark, Pig, Hive, Sqoop, OOZIE, and FLUME
Design both functional and non-functional requirements for working with big data
Understand common business cases for big data
Differentiate between hype and what’s truly possible
Look at examples of real-world big data use cases
Select initiatives and projects that have high potential to benefit from big data applications
Understand what type of staffing, technical skills, and training is required for projects that incorporate or focus on big data
Implementing Big Data & AI for Business Professionals (TTML5501)
AI in Business Seminar Series: Explore How AI & Machine …
What you'll learn
Learn which data is most useful to collect now and why it’s important to start collecting that data as soon as possible
Understand the intersection between big data, data science and AI (Machine Learning / Deep Learning) and how they can help you reach your business goals and gain a competitive advantage.
Understand the factors that go into choosing a Data Science system, including whether to go with a cloud-based solution
Explore common tools and technologies to aid in making informed decisions
Gain the skills required to build your DS/ AI team
Machine Learning Essentials with Python (TTML5506-P)
Learn how Artificial Intelligence is being applied in modern business. …
What you'll learn
Popular machine learning algorithms, their applicability and limitations
Practical application of these methods in a machine learning environment
Practical algorithm use cases and limitations
Exploring AI & Machine Learning for the Enterprise (TTML5500)
Learn how Artificial Intelligence is being applied in modern business. …
What you'll learn
What AI is and what it isn’t
The different types and sub-fields of AI
The differences between Machine Learning, Expert Systems, and Neural Networks
The latest in applied theory
How AI is used in processing language, images, audio, and the web
The current generation of tools used in the marketplace
What’s next in applied AI for businesses
