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Training courses and workshops delivered by industry experts, courses include Big Data, Applied Data Science, Data Analytics, NoSQL, Hadoop, GDPR, SQL Fundamentals and MySQL.
Our Data training courses can be customised to suit your team’s current skill level and key business objectives. See below or why not Contact Us if you wish to have a bespoke course for your team.
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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.
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.
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.
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.
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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.
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.
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.
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.
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 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.
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.
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 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.
This two-day Apache Kafka for Operators training course is for administrators and DevOps-engineers who want to set up and operate Kafka successfully in production. In addition to the most important aspects of operation, participants will also deepen their expertise on how to monitor Kafka and how to avoid catastrophic situations.
Data Science Projects with Python training course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You’ll discover how to tune the algorithms to provide the best predictions on new and, unseen data.
In this two-day Apache Kafka for Developers training course you will experience and learn Kafka in a way that enables you to use it successfully in your company directly afterwards the training. Not only will you gain necessary theoretical knowledge but also practical experience through numerous exercises.
This Data Science for Solution Architects training course helps Solution Architects and other IT practitioners understand the value proposition, methodology and techniques of the emerging discipline of Data Science. The class also introduces the students to a number of existing production-ready technologies and capabilities that enable enterprises to build cost-efficient Big Data processing solutions.
Python has emerged as a popular and effective language in the world of data science. The dynamic nature of the language, the relative simplicity of the syntax, and the abundance of fast and powerful libraries have all been important contributory factors in this growth.
This Python Data Science training course takes a detailed look at the most popular Python libraries for numeric processing, statistical analysis, machine learning, and visualization. We also show how to make use of common Python data types and algorithms to achieve real-world tasks.
Kafkas focus on performance and persistence enables companies to rethink their IT architecture. This introduces new challenges for architects and operators.
In this instructor-led course you will not only experience what makes Kafka such a successful streaming platform but also how to identify challenges and obstacles and how to resolve them as easily as possible.
The EU General Data Protection Regulation (GDPR) is new legislation that provides a single, harmonised data privacy law for the European Union. The GDPR will replace the current Directive and will be directly applicable from 25 May 2018 in all Member States. The GDPR will affect every organisation that processes EU residents' personally identifiable information (PII). The EU General Data Protection Regulation (GDPR) training course also imposes obligations on companies to not only document and safeguard information on identifiable living persons but companies must also be able to evidence compliance
With the increasing risk of data breaches and cyber-attacks, the GDPR aims to prevent the loss of personal data by improving data security for all individuals living in EU member states.
This Apache Hadoop Training Hadoop Programming on the Cloudera Platform training course introduces the students to Apache Hadoop and key Hadoop ecosystem projects: Pig, Hive, Sqoop, Impala, Oozie, HBase, and Spark.
This Apache Hadoop for Systems Administrators training course covers the essentials of deploying and managing an Apache™ Hadoop® cluster. The course is lab intensive with each participant creating their own Hadoop cluster using either the CDH (Cloudera's Distribution, including Apache Hadoop) or Hortonworks Data Platform stacks. Core Hadoop services are explored in depth with emphasis on troubleshooting and recovering from common cluster failures. The fundamentals of related services such as Ambari, Zookeeper, Pig, Hive, HBase, Sqoop, Flume, and Oozie are also covered. The course is approximately 60% lecture and 40% labs.
In this PHP and MySQL training course, students will learn to create database-driven websites using PHP and MySQL or the database of their choice. The class also covers SQL basics.
This MySQL Administration training course teaches the configuration, security management, administration, backup and restore, and optimization of MySQL databases.
MySQL Administration and Development training course is the open source community’s most popular Relational Database Management System (RDBMS) offering, and is a key part of LAMP – Linux™, Apache™, MySQL®, PHP/Perl/Python®. Many Fortune 500 companies adopt MySQL to reap the benefits of an open source, platform-independent RDMS, such as simplifying conversion from other platforms and lowering database Total Cost of Ownership by 90%. This class encourages the student to explore database fundamentals, as well as MySQL features. Students learn the basics of MySQL use and the programming of stored routines and triggers. Students also participate in database design discussions, perform administrative functions, learn about optimization and performance tuning, and explore various APIs. This course covers MySQL 5.0.
This Training in SQL Server 2018 Integration Services course will enable delegates to master SQL Server Integration Services. Delegates also will be able to import and export data using a variety of formats, including Excel spreadsheets and CSV files. The course will cover using the SSIS designer to copy and transforms data.
This instructor-led 2-day SQL Fundamentals training course is designed for students new to writing SQL queries. A typical student will need to learn SQL to build applications or to generate business reports. For the most part, the SQL learned in the course is applicable to all major databases. In the few cases in which there are differences between the databases, these differences will be pointed out.
4 Top Takeaways from the Course:
Make your existing data work harder for you
Get the right report to the right person
Create eloquent reports from raw data
Improve communication inside and outside your organisation
Developers, analysts and business users need to quickly analyse large amounts of data, get insight into that data, retrieve hidden knowledge inside it, and report against various data sources professionally and effectively. This Training in SQL Server Business Intelligence course will enable them to do this with SQL Server Business Intelligence. The 5 day course will cover the SQL Server components and tools used for B.I. projects. The course will also include the new features in SQL Server B.I. 2018. Reporting Services, Analysis Services and Integration Services will be explored and worked with. Components of Business Intelligence in SQL Server are completely independent from the SQL Server databases, so they can be used over any data sources. Therefore it is not necessary to know the SQL Server itself.
Expanding on the Step 2 training, this classroom and labs based session introduces you to the world of Machine Learning.
The creation of data-backed visualizations is a key way data scientists, or any professional, can explore, analyze, and report insights and trends from data. This Microsoft® Power BI® Data Analysis Professional training course software is designed for this purpose. Power BI was built to connect to a wide range of data sources, and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Power BI's data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, allowing users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action.
Expanding on the Step 3 training, this classroom and labs based session introduces you to the world of Deep Learning.
This Pathway to Predictive Analytics Foundation Step 1 Foundation training course combines classroom and lab based exercises that will give you all the foundational knowledge you need to start your predictive analytics journey.
This Pathway to Predictive Analytics – Step 2 Statistics training course, classroom and lab based training, expands upon the foundational training to introduce you to the world of predictive analytics via statistics.
This Predictive Analytics Educational Hack training course covers the four steps of the Pathway to Predictive Analytics and culminates, on the Friday, with a day long hack, combining everything you’ve learned in order to solve a predictive analytics problem. Each group will then present their methodology and findings to the class.
This Predictive Analytics Landscape training course is a level set for executives, managers and business owners, who need to understand the impact that Artificial Intelligence, Machine Learning and Predictive Analytics will have on their business.
This Data Wrangling with Python training course starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You’ll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you’ll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets.
This Introduction to SQL Programming training course is an introduction to the SQL database language. After this course the student will be able to use SQL to define, manipulate and control access to their data. The course thoroughly covers SQL syntax and facilities.The course begins with a general introduction to databases, including the principles of relational databases. Data retrieval is discussed in depth, covering all of the pertinent features of SQL, including joins. Data Manipulation Language is covered, including inserting, updating and deleting data. Transaction control and locking is discussed. Data Definition Language is covered, including creating, altering and dropping tables, and the use of integrity constraints. Views and indexes are covered.
In this SQL Querying training course you learned the basics of SQL querying. In this course, you will build on this foundation, learning advanced querying techniques, such as writing nested queries, using JOINs to combine data from multiple tables, summarizing query results, using advanced filtering, and using views to simplify repetitive querying tasks. You will also learn how to perform common database administration tasks such as duplicating tables, modifying table structures, inserting, updating, or deleting data, and indexing tables to optimize query performance. You will also learn how to work with multiple tasks as a transaction.
This Introduction to MySQL Databases training course teaches the configuration, security management, administration, backup and restore, and optimization of MySQL databases.
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"Absolutely fantastic training. Thoroughly enjoyed it thanks to our highly enthusiastic tutor. It wouldn't be an understatement to say that it was the best professional training that I have ever received."
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
“The course was held at the highest possible standards, the instructor was excellent, well prepared, well informed, and clearly an SME. Top marks.”
Professional Cloud Service Manager - GTC13
Live Online December 2021
“Very engaging and practical course so hope to be able to put the learning into practice.”
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
"Intelligence is the ability to avoid doing work, yet
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Linus Torvalds, creator of Linux and GIT
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28th - 31st March
This Kubernetes Administration Certification training course is suitable for anyone who wants to learn the skills necessary to build and administer a Kubernetes cluster
25th - 28th April
This Linux certification training course teaches in-depth skills in the basics of Linux Administration.
27th - 28th March
IT teams must improve service reliability and system resiliency. With automation and observability becoming key factors for more efficient and rapid deployments, the SRE profile has become one of the fastest-growing job roles.
INTRO TO PYTHON 3
28th - 30th March
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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