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KN3 offer cheap, reduced prices on scheduled Database and Business Intelligence computer training certification courses in key locations around London and the UK.
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Hadoop is more than just a couple technologies such as Hive and Spark; it’s an entire ecosystem of tools that can generate business value. This 3-day Big Data Analytics course gives attendees the essential skills to develop analytical applications using Big Data tools such as Apache Hive, Apache Spark, Presto, Apache NiFi, and Kylo. Our goal is to make students productive in modern Hadoop concepts and tools, while setting the stage for their future growth as a Hadoop developer. This course provides the essential grounding in the principles of Hadoop, the Hadoop Distributed File System (HDFS) storage engine, the roles of new Hadoop computation models such as Spark, and how to write applications effectively using these tools. If your developers are new to Hadoop, they’ll learn the skills necessary to start using Hadoop and integrating it with your existing capabilities. During this 3-day course, each student will have access to their own Amazon Web Services Elastic MapReduce (AWS EMR) cluster to gain hands-on experience with Hadoop. We will also provide students with configuration information necessary for them to create and use identically configured AWS EMR clusters after they have completed the course. Who is the course for Analytics Developers and Data Engineers wishing to learn how to apply Big Data tools in their analyses .. more here
Introduction to Data Science and mathematical models underpinning Big Data Technologies. Deep introduction to working with range of big data tools.
Target AudienceFor existing python developers and data analysts looking to up-skill into big data. .. more here
Fundamentals of Data Science is a three day overview course which blends discussion and group exercises to explore the field of data science with applied real world examples and projects. Teaching begins with a conceptual introduction to science, data science, big data and machine learning; followed by a litany of real-world data science and machine learning examples. The remainder is divided into two parts: python-illustrated and r-illustrated. After introducing both languages, the modules cover various applied topics (data preparation, statistics, Markov chains, neural nets) with examples in either python or R. .. more here
Introduction to R and data analytics. Deeper Introduction to Machine Learning.
Target AudienceAimed at people with existing technological and mathematical background looking to get a quick exposure to mathematics and techniques of Machine Learning. .. more here
Introduction to R, and broad coverage of mathematics for Data Science and Machine Learning: algebra, linear algebra, calculus, probability and statistics.
Target AudienceAimed at fledging data scientists who wish to have a proper understanding of the underlining mathematics and algorithms behind Machine Learning and data analytics. .. more here
Introduction to Python, Data Science and Big Data. Deep introduction to major Big Data technology for practitioners working with them.
Target AudiencePractitioners of data analysis and fledging data scientists who wish to leverage Big Data technologies such as NoSQL databases, Hadoop and Spark. .. more here
Introduction to Statistics, R, Python, Analytics, Data Science and Machine Learning. Sets up practitioners with working knowledge of whole field of data science, along with immediate practical knowledge of key analytical tasks.
Target AudienceFor fledging data science practitioners, and for IT professionals who wish to move to the exiting world of data analytics and machine learning. .. more here
Introduction to R and Python programming languages. Deep coverage of mathematics, algorithms and technology of Machine learning.
Target AudienceThis course is aimed at fledging Machine Learning practitioners, and data analysts who wish to gain more in depth knowledge of Machine Learning. .. more here
Both Data Science and Big Data have risen to prominence recently. Whilst they are not immutably linked, it is certainly true that many data scientists work extensively with big data. Both topics are so new that they are poorly understood; nevertheless there is considerable interest in both and there is a significant shortfall in the number of trained data scientists in the job market. This course introduces both the job role of the data scientist and will help develop familiarisation with big data. The course is vendor neutral; it is not about how to use any vendor's products, it is about the fundamental underpinnings of these two important subject areas.
This course is intended for people aspiring to be data scientists and/or to work with Big Data. Others who may take this course include Business Intelligence (BI) professionals who want to work with big data and/or are looking to move into Data Science. People coming into the course are expected to have at least 3 years experience working in the IT field—typically in the areas of databases, BI, analytics or related areas.. more here