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Big Data and Data Science draws a lot of attention nowadays. By attending our Big Data training courses, we can equip you with the knowledge so you are much better positioned to make informed tactical and strategic decisions critical in today’s very competitive world.
This Advanced Analytics for Structured Data using AWS 2 day course provides a technical introduction to the understanding, creation and digital data supply chains for advanced analytics with AWS.
The Big Data Foundation certification (BDF) is designed to provide you with hands-on experience in using two of the most popular technologies in Big Data processing – Hadoop and MongoDB. You will get the opportunity to practice installing these two technologies through lab exercises. The exercises expose you to real-life Big Data technologies with the purpose of obtaining results from real datasets from Twitter. This Big Data Foundation Certification training course is designed to provide candidates with a well-rounded understanding of big data. It covers the potential data sources that can be used for solving real business problems and an overview of data mining and the tools used in it.
Technology and the data that it both collects and makes accessible is now interwoven with businesses and lives. The era of "big data" has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantage.Analyzing data to find issues, insights and opportunities, is now a critical part of many job roles. Beyond the analysis, data analysts in all job roles must be able to effectively present and communicate their findings in visually compelling ways.
The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms. By leveraging data science concepts and technologies, businesses can mold all of that raw data into information that facilitates decisions to improveand expand the success of the business.
This Data Science for Business Professionals training course is also designed to assist learners in preparing for the CertNexus® DSBIZ™ (Exam DSZ-110) credential.
Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions.
This course begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you’ll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. By working through interesting activities, you’ll explore data encoders and latent variable models.
Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control this data avalanche for you. In this course, you’ll learn practical techniques to aggregate data into useful dimensions for posterior analysis, extract statistical measurements, and transform datasets into features for other systems.
Data is one of the most valuable assets that your organization possesses. Every day you are creating more data and potentially passing up opportunities to harvest that data and use it to accelerate the achievement of your organization’s strategic objectives. Big Data and Analytics represent an emerging trend around harvesting, analyzing, and capitalizing on the wealth of data that is within the grasp of your enterprise. This Big Data and Analytics for Business Users training course introduces Cloud Computing, Big Data, and the emerging discipline of Data Analytics. Attention will be given to the three V’s of Big Data: Volume, Velocity, and Variety as well as the fourth V of Value.
Data Science for Marketing Analytics training course covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments.The course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you’ll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation.
Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning.
This intensive R Programming Introduction training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice.
Success of many organizations depends on their ability to derive business insights from massive amount of raw data coming from various sources.
This Spark Fundamentals training course offers many engineering improvements over the traditional MapReduce programming model as implemented in Hadoop by providing multi-pass in-memory processing of data which boosts the overall performance of your ETL and machine-learning algorithms.
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This Database Design training course introduces a process for effectively planning and designing a functional, efficient database. Knowing how to plan a relational database is important to the success of the databases you create. Without planning, you cannot possibly know what the database needs to do, or even what information to include in the database. Planning a database is essential and prevents the extra work of fixing data maintenance problems later on.
This Hadoop Programming on the Hortonworks Data Platform training course introduces the students to Apache Hadoop and key Hadoop ecosystem projects: Pig, Hive, Sqoop, Oozie, HBase, and Spark.
This intensive training course uses lectures and hands-on labs that help students learn theoretical knowledge and gain practical experience of Apache Hadoop and related Apache projects.
This Introduction to Big Data and NoSQL training course provides an introduction to Big Data as well as NoSQL (Not Only SQL) database systems. The fundamental concepts of and ideas behind Big Data / NoSQL technologies are methodically explored and many buzzwords demystified. The course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the subject.
Applied Data Visualization with R training course and GGPLOT2 is an open-source package for the R programming language that employs the concept of the Grammar of Graphics to help users build complex and aesthetic visualizations.This course begins by introducing you to basic concepts, such as the Grammar of Graphics and geometric objects. It then goes on to explain these concepts in detail with examples. Once you are comfortable with basics, you can learn all about the advanced plotting techniques, such as box plots and density plots. With this course, you can transform data into useful material and make data analysis interesting and fun.This course perfectly balances theory and exercises. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.
This Applied Data Science and Big Data Analytics intensive training course provides theoretical and technical aspects of Data Science and Business Analytics. The course covers the fundamental and advanced concepts and methods of deriving business insights from big” and/or “small” data. This training course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the learned material.
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This Data Science with Python training course provides theoretical and practical aspects of using Python in the realm of Data Science, Business Analytics, and Data Logistics. The coverage of the related core concepts, terminology, and theory is provided as well. This intensive training course is supplemented by a variety of hands-on labs (the list of which is provided at the bottom of this outline) that help attendees reinforce their theoretical knowledge of the learned material.
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Customised Linux with Networking
Live Online - February 2022
"The course content was very good. When needed, the Instructor was extending the content of the course with hints and tips to help us understand different topics that were covered in the course."
Kubernetes Administration Certification - GTLFK
Live Online June 2021
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Professional Cloud Service Manager - GTC13
Live Online December 2021
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Being Agile in Business - GTBAB
Live Online September 2021
“Great instructor, who encouraged active participation. The breakout groups and exercises kept the group engaged and the content relevant to our own products”.
Site Reliability Engineering Foundation - GTDSRE
Live Online January 2022
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13th June - 16th June
This Kubernetes Administration Certification training course is suitable for anyone who wants to learn the skills necessary to build and administer a Kubernetes cluster
6th - 9th June
This LPIC-1 Part 2 Linux Administrator Certification training course prepares students to take the LPI 102-500 exam of the LPIC-1 certification.
26th - 27th June
DevOps Foundation is intended to provide individuals with an understanding of basic DevOps concepts and how DevOps may be used to improve communication, collaboration and integration between software developers and IT operations professionals.
INTRO TO PYTHON 3
23rd - 25th May
6th - 8th June
15th - 17th August
A comprehensive introduction to the core syntax and functions provided by Python, including coverage of its object-oriented and functional programming features.
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