Microsoft MCSA: Machine Learning - Only 6 Days

Why

Seven reasons why you should sit your course with Firebrand Training

Find Out How We Help You To Learn New Skills Quickly

  1. You'll be MCSA Machine Learning certified in just 6 days. With us, you’ll be MCSA Machine Learning trained in record time
  2. Our MCSA Machine Learning course is all-inclusive. A one-off fee covers all course materials, exams, accommodation and meals. No hidden extras
  3. Pass MCSA Machine Learning first time or train again for free. This is our guarantee. We’re confident you’ll pass your course first time. But if not, come back within a year and only pay for accommodation, exams and incidental costs
  4. You’ll learn more. A day with a traditional training provider generally runs from 9am – 5pm, with a nice long break for lunch. With Firebrand Training you’ll get at least 12 hours/day quality learning time, with your instructor
  5. You’ll learn MCSA Machine Learning faster. Chances are, you’ll have a different learning style to those around you. We combine visual, auditory and tactile styles to deliver the material in a way that ensures you will learn faster and more easily
  6. You’ll be studying MCSA Machine Learning with the best. We’ve been named in Training Industry’s “Top 20 IT Training Companies of the Year” every year since 2010. As well as winning many more awards, we’ve trained and certified 70.652 professionals, and we’re partners with all of the big names in the business
  7. You'll do more than study Firebrand's courseware. We use practical exercises to make sure you can apply your new knowledge to the work environment. Our instructors use demonstrations and real-world experience to keep the day interesting and engaging

Think you are ready for the course? Take a FREE practice test to assess your knowledge!

What

Your accelerated MCSA: Machine Learning course will teach you skills in operationalising Microsoft Azure machine learning and Big Data with R Server and SQL R Services. You'll learn to process and analyse large data sets using R and use Azure cloud services to build and deploy intelligent solutions.

Your expert Microsoft Certified Trainer (MCT) will immerse you in the course. You will learn through Firebrand's unique Lecture | Lab | Review technique - helping you to build and retain knowledge faster than traditional training styles. You will develop practial skills relevant to real world application, getting hands-on with Microsoft R Server, SQL R Services, Azure Machine Learning, Cognitive Services and Bot Framework technologies.

You'll cover a range of big data, Microsoft R and cloud data science topics including:

  • How to read, explore and process big data
  • Building predictive models with ScaleR
  • Developing machine learning models
  • Preparing data for analysis in Azure machine learning
  • How to operationalise and manage Azure machine learning services

During your 6-day accelerated MCSA course, you'll also be prepared for exams 70-773: Analyzing Big Data with Microsoft R and 70-774: Perform Cloud Data Science with Azure Machine Learning. You'll sit both exams at the Firebrand training centre during the course. Covered by your Certification Guarantee.

The MCSA Machine Learning certification is designed for those looking to demonstrate their expertise using R and Azure Machine Learning - best suited to data science or data analyst job roles. Achieving the MCSA certification will act as the first step to becoming a Data Management and Analytics Microsoft Certified Solutions Expert (MCSE).

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Use your free Microsoft training vouchers

You may be entitled to heavily-discounted training via Microsoft's Software Assurance Training Voucher (SATV) scheme. If your business has bought Microsoft software, check to see if it came bundled with free training vouchers! Vouchers can be exchanged against training for all Microsoft technologies. If you’re unsure, get in touch with us

Other accelerated training providers rely heavily on lecture and independent self-testing and study.

Effective technical instruction must be highly varied and interactive to keep attention levels high, promote camaraderie and teamwork between the students and instructor, and solidify knowledge through hands-on learning.

Firebrand Training provides instruction to meet every learning need:

  • Intensive group instruction
  • One-on-one instruction attention
  • Hands-on labs
  • Lab partner and group exercises
  • Question and answer drills
  • Independent study

This information has been provided as a helpful tool for candidates considering training. Courses that include certification come with a Certification Guarantee. Pass first time or train again for free (just pay for accommodation, exams and incidental costs). We do not make any guarantees about personal successes or benefits of obtaining certification. Benefits of certification determined through studies do not guarantee any particular personal successes.

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Course 20773A: Analysing Big Data with Microsoft R


Module 1: Microsoft R Server and R Client

Explain how Microsoft R Server and Microsoft R Client work.

Lessons

  • What is Microsoft R server
  • Using Microsoft R client
  • The ScaleR functions

Lab : Exploring Microsoft R Server and Microsoft R Client

  • Using R client in VSTR and RStudio
  • Exploring ScaleR functions
  • Connecting to a remote server

After completing this module, you’ll be able to:

  • Explain the purpose of R server.
  • Connect to R server from R client
  • Explain the purpose of the ScaleR functions.

Module 2: Exploring Big Data

At the end of this module the student will be able to use R Client with R Server to explore big data held in different data stores.

Lessons

  • Understanding ScaleR data sources
  • Reading data into an XDF object
  • Summarising data in an XDF object

Lab : Exploring Big Data

  • Reading a local CSV file into an XDF file
  • Transforming data on input
  • Reading data from SQL Server into an XDF file
  • Generating summaries over the XDF data

After completing this module, you’ll be able to:

  • Explain ScaleR data sources
  • Describe how to import XDF data
  • Describe how to summarise data held in XCF format

Module 3: Visualising Big Data

Explain how to visualize data by using graphs and plots.

Lessons

  • Visualising In-memory data
  • Visualising big data

Lab : Visualizing data

  • Using ggplot to create a faceted plot with overlays
  • Using rxlinePlot and rxHistogram

After completing this module, you’ll be able to:

  • Use ggplot2 to visualise in-memory data
  • Use rxLinePlot and rxHistogram to visualise big data

Module 4: Processing Big Data

Explain how to transform and clean big data sets.

Lessons

  • Transforming Big Data
  • Managing datasets

Lab : Processing big data

  • Transforming big data
  • Sorting and merging big data
  • Connecting to a remote server

After completing this module, you’ll be able to:

  • Transform big data using rxDataStep
  • Perform sort and merge operations over big data sets

Module 5: Parallelising Analysis Operations

Explain how to implement options for splitting analysis jobs into parallel tasks.

Lessons

  • Using the RxLocalParallel compute context with rxExec
  • Using the revoPemaR package

Lab : Using rxExec and RevoPemaR to parallelise operations

  • Using rxExec to maximise resource use
  • Creating and using a PEMA class

After completing this module, you’ll be able to:

  • Use the rxLocalParallel compute context with rxExec
  • Use the RevoPemaR package to write customised scalable and distributable analytics.

Module 6: Creating and Evaluating Regression Models

Explain how to build and evaluate regression models generated from big data

Lessons

  • Clustering Big Data
  • Generating regression models and making predictions

Lab : Creating a linear regression model

  • Creating a cluster
  • Creating a regression model
  • Generate data for making predictions
  • Use the models to make predictions and compare the results

After completing this module, you’ll be able to:

  • Cluster big data to reduce the size of a dataset.
  • Create linear and logit regression models and use them to make predictions.

Module 7: Creating and Evaluating Partitioning Models

Explain how to create and score partitioning models generated from big data.

Lessons

  • Creating partitioning models based on decision trees.
  • Test partitioning models by making and comparing predictions

Lab : Creating and evaluating partitioning models

  • Splitting the dataset
  • Building models
  • Running predictions and testing the results
  • Comparing results

After completing this module, you’ll be able to:

  • Create partitioning models using the rxDTree, rxDForest, and rxBTree algorithms.
  • Test partitioning models by making and comparing predictions.

Module 8: Processing Big Data in SQL Server and Hadoop

Explain how to transform and clean big data sets.

Lessons

  • Using R in SQL Server
  • Using Hadoop Map/Reduce
  • Using Hadoop Spark

Lab : Processing big data in SQL Server and Hadoop

  • Creating a model and predicting outcomes in SQL Server
  • Performing an analysis and plotting the results using Hadoop Map/Reduce
  • Integrating a sparklyr script into a ScaleR workflow

After completing this module, you’ll be able to:

  • Use R in the SQL Server and Hadoop environments.
  • Use ScaleR functions with Hadoop on a Map/Reduce cluster to analyse big data.

Course 20774A: Perform Cloud Data Science with Azure Machine Learning


Module 1: Introduction to Machine Learning

This module introduces machine learning and discussed how algorithms and languages are used.

Lessons

  • What is machine learning?
  • Introduction to machine learning algorithms
  • Introduction to machine learning languages

Lab : Introduction to machine Learning

  • Sign up for Azure machine learning studio account
  • Run a simple experiment from gallery
  • Evaluate an experiment

After completing this module, you’ll be able to:

  • Describe machine learning
  • Describe machine learning algorithms
  • Describe machine learning languages

Module 2: Introduction to Azure Machine Learning

Describe the purpose of Azure Machine Learning, and list the main features of Azure Machine Learning Studio.

Lessons

  • Azure machine learning overview
  • Introduction to Azure machine learning studio
  • Developing and hosting Azure machine learning applications

Lab : Introduction to Azure machine learning

  • Explore the Azure machine learning studio workspace
  • Clone and run a simple experiment
  • Clone an experiment, make some simple changes, and run the experiment

After completing this module, you’ll be able to:

  • Describe Azure machine learning.
  • Use the Azure machine learning studio.
  • Describe the Azure machine learning platforms and environments.

Module 3: Managing Datasets

At the end of this module the student will be able to upload and explore various types of data in Azure machine learning.

Lessons

  • Categorizing your data
  • Importing data to Azure machine learning
  • Exploring and transforming data in Azure machine learning

Lab : Visualizing Data

  • Prepare Azure SQL database
  • Import data
  • Visualize data
  • Summarize data

After completing this module, you’ll be able to:

  • Understand the types of data they have.
  • Upload data from a number of different sources.
  • Explore the data that has been uploaded.

Module 4: Preparing Data for use with Azure Machine Learning

This module provides techniques to prepare datasets for use with Azure machine learning.

Lessons

  • Data pre-processing
  • Handling incomplete datasets

Lab : Preparing data for use with Azure machine learning

  • Explore some data using Power BI
  • Clean the data

After completing this module, you’ll be able to:

  • Pre-process data to clean and normalise it.
  • Handle incomplete datasets.

Module 5: Using Feature Engineering and Selection

This module describes how to explore and use feature engineering and selection techniques on datasets that are to be used with Azure machine learning.

Lessons

  • Using feature engineering
  • Using feature selection

Lab : Using feature engineering and selection

  • Merge datasets
  • Use PCA to reduce dimensions
  • Select some variables and edit metadata

After completing this module, you’ll be able to:

  • Use feature engineering to manipulate data.
  • Use feature selection.

Module 6: Building Azure Machine Learning Models

This module describes how to use regression algorithms and neural networks with Azure machine learning.

Lessons

  • Azure machine learning workflows
  • Scoring and evaluating models
  • Using regression algorithms
  • Using neural networks

Lab : Building Azure machine learning models

  • Using Azure machine learning studio modules for regression
  • Evaluate machine learning models
  • Add further regression models
  • Create and run a neural-network based application

After completing this module, you’ll be able to:

  • Describe machine learning workflows.
  • Explain scoring and evaluating models.
  • Describe regression algorithms.
  • Use a neural-network.

Module 7: Using Classification and Clustering with Azure machine learning models

This module describes how to use classification and clustering algorithms with Azure machine learning.

Lessons

  • Using classification algorithms
  • Clustering techniques
  • Selecting algorithms

Lab : Using classification and clustering with Azure machine learning models

  • Using Azure machine learning studio modules for classification.
  • Add k-means section to an experiment
  • Add PCA for anomaly detection.
  • Evaluate the models

After completing this module, you’ll be able to:

  • Use classification algorithms.
  • Describe clustering techniques.
  • Select appropriate algorithms.

Module 8: Using R and Python with Azure Machine Learning

This module describes how to use R and Python with azure machine learning and choose when to use a particular language.

Lessons

  • Using R
  • Using Python
  • Using Jupyter notebooks
  • Supporting R and Python

Lab : Using R and Python with Azure machine learning

  • Adding R and Python scripts
  • Using Python with Visual Studio IDE
  • Add a Jupyter notebook
  • Run Jupyter notebook
  • Import packages for R/Python
  • Data visualisation using R/Python
  • R programming to work on a time series

After completing this module, you’ll be able to:

  • Explain the key features and benefits of R.
  • Explain the key features and benefits of Python.
  • Use Jupyter notebooks.
  • Support R and Python.

Module 9: Initialising and Optimising Machine Learning Models

This module describes how to use hyper-parameters and multiple algorithms and models, and be able to score and evaluate models.

Lessons

  • Using hyper-parameters
  • Using multiple algorithms and models
  • Scoring and evaluating ensembles

Lab : Initialising and optimising machine learning models

  • Using hyper-parameters
  • Build an ensemble using stacking
  • Evaluate the ensemble

After completing this module, you’ll be able to:

  • Use hyper-parameters.
  • Use multiple algorithms and models to create ensembles.
  • Score and evaluate ensembles.

Module 10: Using Azure Machine Learning Models

This module explores how to provide end users with Azure machine learning services, and how to share data generated from Azure machine learning models.

Lessons

  • Deploying and publishing models
  • Exporting data

Lab : Using Azure machine learning models

  • Deploy machine learning models
  • Consume a published model
  • Export data
  • Use exported data in machine learning model

After completing this module, you’ll be able to:

  • Deploy and publish models.
  • Export data to a variety of targets.

Module 11: Using Cognitive Services

This module introduces the cognitive services APIs for text and image processing to create a recommendation application, and describes the use of neural networks with Azure machine learning.

Lessons

  • Cognitive services overview
  • Processing text
  • Processing images
  • Creating recommendations

Lab : Using Cognitive Services

  • Create and run a text processing application
  • Create and run an image processing application
  • Create and run a recommendation application

After completing this module, you’ll be able to:

  • Describe cognitive services.
  • Process text through an application.
  • Process images through an application.
  • Create a recommendation application.

Module 12: Using Machine Learning with HDInsight

This module describes how use HDInsight with Azure machine learning.

Lessons

  • Introduction to HDInsight
  • HDInsight cluster types
  • HDInsight and machine learning models

Lab : Machine Learning with HDInsight

  • Deploy an HDInsight cluster
  • Use the HDInsight cluster
  • Display data in Power BI

After completing this module, you’ll be able to:

  • Describe the features and benefits of HDInsight.
  • Describe the different HDInsight cluster types.
  • Use HDInsight with machine learning models.

Module 13: Using R Services with Machine Learning

This module describes how to use R and R server with Azure machine learning, and explain how to deploy and configure SQL Server and support R services.

Lessons

  • R and R server overview
  • Using R server with machine learning
  • Using R with SQL Server

Lab : Using R services with machine learning

  • Deploy DSVM
  • Explore the data science VM
  • Configure R server
  • Run a sample R server application
  • Deploy a SQL server 2016 Azure VM
  • Configure SQL Server to allow execution of R scripts
  • Execute R scripts inside T-SQL statements
  • Use R to visualise data

After completing this module, you’ll be able to:

  • Implement interactive queries.
  • Perform exploratory data analysis.

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You will sit the following exams on-site, during the course. Covered by your Certification Guarantee.

Exam 70-773: Analyzing Big Data with Microsoft R

Technology: Microsoft R Server, SQL R Services

Languages: English

Skills measured:

  • Read and explore big data
  • Process big data
  • Build predictive models with ScaleR
  • Use R Server in different environments

Exam 70-774: Perform Cloud Data Science with Azure Machine Learning

Technology: Azure Machine Learning, Bot Framework, Cognitive Services

Languages: English

Skills measured:

  • Prepare Data for Analysis in Azure Machine Learning and Export from Azure Machine Learning
  • Develop Machine Learning Models
  • Operationalise and Manage Azure Machine Learning Services
  • Use Other Services for Machine Learning

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Firebrand Training offers top-quality technical education and certification training in an all-inclusive course package specifically designed for the needs and ease of our students. We attend to every detail so our students can focus solely on their studies and certification goals.

Our Accelerated Learning Programmes include:

  • Intensive Hands-on Training Utilising our (Lecture | Lab | Review)TM Delivery
  • Comprehensive Study Materials, Program Courseware and Self-Testing Software including MeasureUp *
  • Fully instructor-led program with 24 hour lab access
  • Examination vouchers **
  • On site testing ***
  • Accommodation, all meals, unlimited beverages, snacks and tea / coffee****
  • Transportation to/from designated local railway stations
  • Examination Passing Policy

Our instructors teach to accommodate every student's learning needs through individualised instruction, hands-on labs, lab partner and group exercises, independent study, self-testing, and question/answer drills.

Firebrand Training has dedicated, well-equipped educational facilities where you will attend instruction and labs and have access to comfortable study and lounging rooms. Our students consistently say our facilities are second-to-none.

Firebrand goes digital

We’re currently migrating from printed to digital courseware. Some courseware is already available in digital, while other books remain in printed form. To find out if this course is digital, call us on +33 (0) 181 22 44 68.

There are several benefits of easy-to-use digital courseware: downloads are immediate, and you’ll always have your courseware available wherever you are. You won’t need to wait for a printed book to be delivered before you start learning – and it’s better for the environment. You can choose to download the courseware to your own device, or borrow one of ours.

Considering a Microsoft course? Always have the most up-to-date Microsoft digital courseware with ‘Fresh Editions’. This gives you access to all versions of digital courseware – you’ll receive updates and revisions of your textbook, at no charge, for the life of that course.

Examination Passing Policy

Should a student complete a Firebrand Training Program without having successfully passed all vendor examinations, the student may re-attend that program for a period of one year.  Students will only be responsible for accommodations and vendor exam fees.

Please note

  • * Not on all courses
  • ** Examination vouchers are not included for the following courses: PMI, GIAC, CREST and CISSP CBK Review. Exam vouchers may also not be included for Apprentices and will require a separate purchase by an employer due to Education and Skills Funding Agency guidelines.
  • *** On site testing is not included for our PMI, GIAC, CREST, CSX Practitioner or ITIL Managers and Revision Certification Courses
  • **** Accommodation not included on the CISSP CBK Review Seminar

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It is recommended you have the following prerequisite skills and knowledge before attending the course:

  • Experience of publishing effective APIs for knowledge intelligence
  • Knowledge of Azure data services and machine learning
  • Familiarity with common data science processes - filtering and transforming data sets, model estimation and model evaluation
  • Experience of working with R - writing and debugging R functions
  • Understanding of data structures
  • Basic knowledge programming concepts - control flow and scope
  • Be familiar with common statistical methods and data analysis best practices
  • A high-level understanding of data platforms - the Hadoop ecosystem, SQL Server and core T-SQL capabilities

Unsure whether you meet the prerequisites?

Don’t worry - we’ll discuss your technical background, experience and qualifications to determine whether this accelerated course suits you.

Just call us on +33 (0) 181 22 44 68 and speak to one of our enrolment consultants.

Firebrand is an immersive environment and requires commitment. Some prerequisites are simply guidelines; you may find your unique experience, attitude and determination enables you to succeed on your accelerated course.

Interested? See prices or call +33 (0) 181 22 44 68

When

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Reviews

Here's the Firebrand Training review section. Since 2001 we've trained exactly 70.652 students and asked them all to review our Accelerated Learning. Currently, 96.74% have said Firebrand exceeded their expectations.

Read reviews from recent accelerated courses below or visit Firebrand Stories for written and video interviews from our alumni.


"The training centre is very well organised and professional, I found the course very detailed and got a lot out of it."
Joseph Naber. - Microsoft MTA Software Development Fundamentals (2 days) (10/1/2019 to 11/1/2019)

"Firebrand training is a good way to get qualifications fast. Be prepared with the self-learning before hand and for long days."
Anonymous. - Microsoft MTA Software Development Fundamentals (2 days) (10/1/2019 to 11/1/2019)

"The course was intense but well delivered, the instructor engaged with the group and took the time to give good feedback and help."
Joseph Naber, Games Workshop. - Microsoft MTA Software Development Fundamentals (2 days) (10/1/2019 to 11/1/2019)

"Highly recommendable course and praise worthy."
W.A.. - Microsoft Azure Academy: Infrastructure and Networking (4 days) (7/1/2019 to 10/1/2019)

"The course is high intensity but still managed to maintain a friendly atmosphere. The residential aspect is definitely beneficial to your learning. "
Anonymous. - Microsoft MTA: Windows Server Administration Fundamentals (3 days) (9/1/2019 to 10/1/2019)

"A good learning environment for people who are looking for a job in the IT depart. Friendly instructor. "
Thomas Thornton. - Microsoft MTA Security, Windows Server Administration & Networking (6 days) (7/1/2019 to 12/1/2019)

"Great teaching but the course was not particularly relevant to our job and skill set. "
Dexter Lee, BBC. - Microsoft MTA Security, Windows Server Administration & Networking (6 days) (7/1/2019 to 12/1/2019)

"Very good facilities, good efficient teaching, would definitely recommend to others that are looking for an IT course."
Andrew Smith, BBC. - Microsoft MTA Security, Windows Server Administration & Networking (6 days) (7/1/2019 to 12/1/2019)

"My instructor was extremely committed to help with our studying, with a group who have had very little experience in the topic our course was based on. The resources provided were also very useful."
Sam Hughes, BBC. - Microsoft MTA Security, Windows Server Administration & Networking (6 days) (7/1/2019 to 12/1/2019)

"Great experience, learnt a huge amount in a short space of time."
Anonymous. - Microsoft Azure Academy: Infrastructure and Networking (4 days) (7/1/2019 to 10/1/2019)

"Good and clear instruction, with interactive discussions suited to students needs. Thoroughly recommended."
Anonymous. - Microsoft Azure Academy: Infrastructure and Networking (4 days) (7/1/2019 to 10/1/2019)

"Training was excellent and the instructor was amazing."
Samson Jesi, NCC Group. - Microsoft Azure Academy: Infrastructure and Networking (4 days) (7/1/2019 to 10/1/2019)

"Key & relevant advice provided by highly knowledge subject matter experts. Better equipped to provide advice to customers deploying solutions within the cloud."
Anonymous. - Microsoft Azure Academy: Infrastructure and Networking (4 days) (7/1/2019 to 10/1/2019)

"Firebrand are the best training provider I have used, with knowledge and engaged instructors. "
M.P.. - Microsoft Azure Academy: Infrastructure and Networking (4 days) (7/1/2019 to 10/1/2019)

"The course was very helpful to me as I do C# at my job. They cover all basic fundamentals. The food here is great as well. The stay was comfortable and flexible. You can stay here easily and learn quickly."
S.Y.. - Microsoft Programming in C# (4 days) (7/1/2019 to 10/1/2019)

"Good facility, nice people and an organised concept. Enjoyed my stay and learnt new skills."
James Vost. - Microsoft MTA HTML5 App Development Fundamentals (2 days) (7/1/2019 to 8/1/2019)

"The training provided was all relevant and useful for me to prepare for the exam. "
Anonymous. - Microsoft MTA HTML5 App Development Fundamentals (2 days) (7/1/2019 to 8/1/2019)

"Training is relevant but extremely intense, there is a lot to take in in a short amount of time. "
Anonymous. - Microsoft MTA HTML5 App Development Fundamentals (2 days) (7/1/2019 to 8/1/2019)

"Intensive training, I would recommend, decent level of experience required, but it worked for me to do that extra knowledge required to become MCSA certified. Thanks."
Barry Mansell, CPTO. - Microsoft MCSA: Windows Server 2016 (11 days) (6/12/2018 to 16/12/2018)

"It is a nice experience at Firebrand."
Anonymous. - Microsoft MCSA: Windows Server 2016 (11 days) (6/12/2018 to 16/12/2018)

"I recommend Firebrand to anyone that is looking to either gain knowledge for the first time or to learn something new."
S.P.. - Microsoft MTA Database Fundamentals (2 days) (12/12/2018 to 13/12/2018)

"Awesome place, awesome instructors, real challenges. This is the Firebrands recipe for success."
V.F.. - Microsoft Architecting Microsoft Azure Solutions (3 days) (8/12/2018 to 10/12/2018)

"Learnt a lot - good course, but very intense. Not for the faint or weak! Very good instructor."
Anonymous. - Microsoft Architecting Microsoft Azure Solutions (3 days) (8/12/2018 to 10/12/2018)

"Good course, long hours, sometimes a little overwhelming to say the least. good atmosphere."
Richard Eaton, Avnet. - Microsoft Architecting Microsoft Azure Solutions (3 days) (8/12/2018 to 10/12/2018)

"Great instructor."
Anonymous. - Microsoft MCSA: Cloud Platform & MCSE: Cloud Platform and Infrastructure (Azure) (10 days) (1/12/2018 to 10/12/2018)

"Extremely effective use of time. Very knowledgeable instructor. Good, focused group."
Mark Townsend, TechSea Ltd. - Microsoft MCSA: Cloud Platform & MCSE: Cloud Platform and Infrastructure (Azure) (10 days) (1/12/2018 to 10/12/2018)

"Good trainer who has lots of experience in the field. Taught at a good pace and got through all off the content."
Jess Chapman, Natures Way Foods. - Microsoft MCSA: Windows Server 2016 (11 days) (6/12/2018 to 16/12/2018)

"Very busy course. Lots of content."
Anonymous, Codurance - Microsoft Developing Microsoft Azure Solutions (4 days) (4/12/2018 to 7/12/2018)

"Great way to study in an intensive learning environment without the distractions often attributed to E Learning."
Daniel Middleditch, React Computer Partnership. - Microsoft Implementing Microsoft Azure Infrastructure Solutions (3 days) (1/12/2018 to 3/12/2018)

"Its Good."
Lyndon Martin, Nottinghamshire Healthcare. - Microsoft MCSA: SQL Server 2016 - Business Intelligence Development (5 days) (26/11/2018 to 30/11/2018)

"I will happily use firebrand again the staff and the teachers are great, its hard work but completely worth it. "
Anonymous. - Microsoft MCSA: SQL Server 2016 - Business Intelligence Development (5 days) (26/11/2018 to 30/11/2018)

"I love training at Firebrand. As a consultant, every day matters as you do not get paid if you do not work. The immersive bootcamp allows myself to cover twice the material in half the time. I also like getting into my bubble by it being residential so I can focus on absorbing and recalling. Great having the test centre onsite.. Maximises exam cram time. Thank you FB Wyboston."
Roy Casella, Designated. - Microsoft MCSA: SQL Server 2016 - Business Intelligence Development (5 days) (26/11/2018 to 30/11/2018)

"I enjoyed my course at Firebrand. The trainers are friendly and extremely knowledgeable. This was my first experience of Microsoft exams and I would not hesitate to recommend Firebrand for anyone looking to achieve certification."
Darren Conley, Nicander Ltd.. - Microsoft MCSA: SQL Server 2016 - Business Intelligence Development (5 days) (26/11/2018 to 30/11/2018)

"Studying with Firebrand is tough, theres no getting away from the fact that the days are long and full of content, however, the trainers are knowledgeable and the training is delivered professionally, in excellent facilities."
Rob Sims. - Microsoft MCSA: SQL Server 2016 - Business Intelligence Development (5 days) (26/11/2018 to 30/11/2018)

"Great experience and staff, training setup and instructor."
K.W., Midwich Ltd. - Microsoft MCSA: SQL Server 2016 - Business Intelligence Development (5 days) (26/11/2018 to 30/11/2018)

"Course had plenty of useful information and very helpful."
Connor Venton, Ringway Jacobs. - Microsoft MCSA: SQL Server 2016 - Business Intelligence Development (5 days) (26/11/2018 to 30/11/2018)

"My experience of this intensive course was a good one! This was due to my instructor who was so helpful and engaged us all from the beginning to the end. Thanks to the instructor for being an amazing , intelligent , funny and caring instructor"
Louise-Clair Elliot, Freightliner. - Microsoft MCSA: BI Reporting (4 days) (22/11/2018 to 25/11/2018)

"This is how training should be imparted especially the accelerated approach. Thanks a ton."
Sanjeev Putla, NA. - Microsoft MCSA: BI Reporting (4 days) (22/11/2018 to 25/11/2018)

"Intense but worth it"
R.V.. - Microsoft Dynamics AX 7 Financials (5 days) (19/11/2018 to 23/11/2018)

"Different type of training and it was intense. Covered many topics in express speed. It was a good learning experience. "
John Jesudason. - Microsoft Managing SharePoint Server 2016 (6 days) (19/11/2018 to 24/11/2018)

"The instructor is a great trainer that will help you understand SharePoint much better and get certified."
Anonymous. - Microsoft MCSE: Productivity (SharePoint Server 2016) (6 days) (19/11/2018 to 24/11/2018)

"I have learn a lot of new things in a short time."
A.P.. - Microsoft MCSA: Web Applications (Developing ASP.NET MVC Web 5 Applications) (3 days) (20/11/2018 to 22/11/2018)

"Great Teacher, Interesting Courses and the instructor Is the best"
Jo Van Vosselen. - Microsoft MCSA: Web Applications (Developing ASP.NET MVC Web 5 Applications) (3 days) (13/9/2018 to 15/9/2018)

"Another great course with the instructor. Very enjoyable and pleasant, lots of knowledge transfer and helpful real-life cases where to apply these techniques. I'm looking forward for another course in the future with him."
Christian Dornetto, CRM Dynamics Ltd. - Microsoft MCSA: Web Applications (Developing ASP.NET MVC Web 5 Applications) (3 days) (20/11/2018 to 22/11/2018)

"Very efficient training course."
Adel Flici, London Metal Exchange. - Microsoft Dynamics 365 Customisation and Configuration (4 days) (14/11/2018 to 17/11/2018)

"Great course, and really engrossing way to learn."
Ben Lewis, Kagool. - Microsoft Implementing Microsoft Azure Infrastructure Solutions (3 days) (14/11/2018 to 16/11/2018)

"The instructor was great yet again. teaching subjects that are not covered, but allows for a better understanding of the course. Highly recommend. "
Anonymous. - Microsoft MTA Security, Windows Server Administration & Networking (6 days) (5/11/2018 to 10/11/2018)

"The course was delivered well and taught a broad range of skills, both exam related and functional."
Anonymous. - Microsoft MTA Security, Windows Server Administration & Networking (6 days) (5/11/2018 to 10/11/2018)

"The courses are very well structured at Firebrand, the instructors are patient and helpful. "
B.M.. - Microsoft Querying Data with Transact-SQL (3 days) (5/11/2018 to 7/11/2018)

"My trainer was very very helpful"
J.T.. - Microsoft MTA Security, Windows Server Administration & Networking (6 days) (5/11/2018 to 10/11/2018)

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