Microsoft MCSA: Machine Learning - Slechts 6 dagen

Zeven redenen waarom jij voor jouw MCSA Machine Learning cursus voor Firebrand kiest:

Bekijk deze video en zie waarom je met Firebrand geld en tijd bespaart

  1. Jij zal in slechts 6 dagen MCSA Machine Learning getrained zijn. Doordat onze cursussen residentieel zijn kunnen wij langere lesdagen aanbieden en zal je tijdens je verblijf volledig gefocust zijn op jouw cursus
  2. Onze MCSA Machine Learning cursus is all-inclusive. Cursusmaterialen, accommodatie en maaltijden zijn inbegrepen.
  3. Slaag de eerste keer voor MCSA Machine Learning of train gratis opnieuw. Vraag naar de voorwaarden van onze certificeringsgarantie bij onze Education Consultants.
  4. Je zal meer over MCSA Machine Learning leren. Waar opleidingen elders doorgaans van 9:00 tot 17:00 duren, kan je bij Firebrand Training rekenen op 12 uur training per dag!

  5. Je zal MCSA Machine Learning sneller beheersen. Doordat onze cursussen residentieel zijn word je in korte tijd ondergedompeld in de theorie. Hierdoor zal je volledig gefocust zijn op de cursus en zal je sneller de theorie en praktijk beheersen.
  6. Je zal voor MCSA Machine Learning studeren bij de beste training provider. Firebrand heeft het Q-For kwaliteitlabel, waarmee onze standaarden en professionaliteit op het gebied van training erkend worden. We hebben inmiddels 64.212 professionals getraind en gecertificeerd!
  7. Je gaat meer doen dan alleen de cursusstof van MCSA Machine Learning bestuderen. We maken gebruik van laboratoria, case-studies en oefentests, om ervoor te zorgen dat jij jouw nieuwe kennis direct in jouw werkomgeving kan toepassen.

Denk jij klaar te zijn voor deze opleiding? Doe een GRATIS oefentest om je kennis te testen!

Wanneer wilt u deelnemen aan een versnelde opleiding?

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22/5/2017 (Maandag)

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25/9/2017 (Maandag)

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6/11/2017 (Maandag)

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18/12/2017 (Maandag)

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29/1/2018 (Maandag)

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12/3/2018 (Maandag)

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Wereldwijd heeft Firebrand in haar 10-jarig bestaan al 64.212 studenten opgeleid! We hebben ze allemaal gevraagd onze versnelde opleidingen te evalueren. De laatste keer dat we onze resultaten analyseerden, bleek 96.51% ons te beoordelen als ‘boven verwachting’

"Zeer veel informatie, maar wel deskundig en duidelijke uitleg!"
Henk Schinkel, geen. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (23/11/2015 t/m 1/12/2015)

"Fijne accomodatie en eten. Zeer ervaren en professionele docent"
Anoniem - Microsoft MCSA: Office 365 (5 Dagen) (26/11/2015 t/m 29/11/2015)

"Prima opleiding geweldige kundige docent uitstekende locatie"
Anoniem - Microsoft MCSA: Office 365 (5 Dagen) (26/11/2015 t/m 29/11/2015)

"You will learn a great deal with Firebrand and have every good chance in passing your chosen exams. Its a very unique experience. "
Anoniem - Microsoft MTA Networking, Security & Windows Server Administration (6 Dagen) (2/11/2015 t/m 7/11/2015)

"Fast Good learning!"
Anoniem - Microsoft MTA Networking, Security & Windows Server Administration (6 Dagen) (2/11/2015 t/m 7/11/2015)

"The instructor was very thorough and professional. He made the course very understandable. I was very impressed with his teaching methods and presentations. Firebrand is the best."
Anoniem - Microsoft MTA Networking, Security & Windows Server Administration (6 Dagen) (2/11/2015 t/m 7/11/2015)

"Great Instructor, much details and good stories from the IT Field. This is for me a drive to continue my IT career and learn more."
Anoniem - Microsoft MTA Networking, Security & Windows Server Administration (6 Dagen) (2/11/2015 t/m 7/11/2015)

"Very good way to pass certification if you're able to study and assimilate new knowledges quickly. "
Anoniem - Microsoft MTA Networking, Security & Windows Server Administration (6 Dagen) (2/11/2015 t/m 7/11/2015)

"Awesome! Great teacher with endless patience!! :)"
Anoniem - Microsoft Querying SQL Server (4 Dagen) (2/11/2015 t/m 5/11/2015)

"Efficient learning with the experience and qualified instructor. Highly recommended!"
Anoniem - Microsoft Querying SQL Server (4 Dagen) (2/11/2015 t/m 5/11/2015)

"Continue the way you are!"
Anoniem - Microsoft Querying SQL Server (4 Dagen) (2/11/2015 t/m 5/11/2015)

"Middelen om de trainingen te volgen zijn uitstekend."
Anoniem, HCG Hoedt - Microsoft Specialist: Implementing Microsoft Azure Infrastructure Solutions (3 Dagen) (16/10/2015 t/m 18/10/2015)

"Firebrand biedt een mooie geisoleerde omgeving, waarin je, gemotiveerd door een vakbekwame en gedreven docent, met medecursisten dag (en nacht) bezig kunt zijn met slechts een ding voor ogen: de cursusinhoud. Hoewel zeker vermoeiend, vind ik de cursussen van Firebrand absoluut de moeite waard in het traject van verkrijgen van vakgerichte kennis en certificering."
Anoniem, erwinbeelen.com - Microsoft Specialist: Implementing Microsoft Azure Infrastructure Solutions (3 Dagen) (16/10/2015 t/m 18/10/2015)

"Really enjoyable and very hard experience. Trainer made the course fun to do."
Anoniem - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (19/9/2015 t/m 27/9/2015)

"Get more in less time"
Anoniem - Microsoft MCSD: SharePoint Applications (12 Dagen) (28/4/2014 t/m 9/5/2014)

"This course was realy good; you lose no time, an efficient way of work"
Philippe De Groote , saphico. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (27/10/2013 t/m 3/11/2013)

"8 Days course which also includes two weekends. Our trainer made it an experience I didn't want to miss!"
Sybrand Hartman, Tata Steel. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (27/10/2013 t/m 3/11/2013)

"Een zeer postitieve ervaring, alles is goed geregeld en de trainer was altijd bereid je vragen te beantwoorden. Je leeft hier echt voor de cursus dwz je staat er mee op en tijdens ontbijt begint het al en je stopt pas als je ogen dicht gaan bij het slapen. Zeer goede manier om kennis op te doen. Veel theorie maar ook wel Hands On!"
CG, Veiligheidsregio Kennemerland. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (9/6/2013 t/m 16/6/2013)

"Thuis studeren had me twee keer zoveel tijd gekost. Op de cursus kon ik me erg goed concentreren op de stof en zo ook mijn certificaten behalen in een zeer korte tijd."
Marc van Berkel, Linfosys. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (9/6/2013 t/m 16/6/2013)

"Prima docent, fijne locatie, maar erg intensief."
MV. - Microsoft MCSE: SharePoint 2013 (6 Dagen) (10/6/2013 t/m 15/6/2013)

"Its always great to be busy with SharePoint for a full week. All my goals are completed and got a very good understanding, learned a lot and cannot wait to start using this best practices in my daily work. Very good teacher with a lot of experience, from different kind of businesses."
Anoniem - Microsoft MCSE: SharePoint 2013 (6 Dagen) (10/6/2013 t/m 15/6/2013)

"Tsunami van informatie en leerstof komt over je heen. Voorbereiden op het assimileren, zeg maar opslorpen, van al deze kennis is een vereiste indien het lang geleden is dat je op de schoolbanken zat. Maar het is een reuze ervaring. Een belevenis en je honger wordt gestild."
Anoniem, VSOA Defensie - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (7/4/2013 t/m 14/4/2013)

"- Tempo ligt erg hoog, de zaterdagavond (niet inbegrepen bij de 8 dagen) is dan ook zeer nodig. - Kom met genoeg kennis! - Kom met een goede motivatie!"
Rob de Haan, Van Dam ICT. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (7/4/2013 t/m 14/4/2013)

"Great teacher, learned a lot and had a good team! Really good way of learning."
Marloes Rutten, SplitVision. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (20/1/2013 t/m 27/1/2013)

"Het is niet gemakkelijk, je krijgt erg veel informatie tegelijk maar met de juiste instelling is het zeker te doen. De MCSA 2012 cursus is zeer de moeite waard en ik kan deze methode en de accomodatie zeker aanbevelen!"
Marc Willemsen, EIC BV. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (20/1/2013 t/m 27/1/2013)

"Goede en krachtige training!"
Chris Carremans, EASI / Appligen. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (4/11/2012 t/m 11/11/2012)

"Je moet met de juiste instelling naar de training komen. Je moet na de lesuren, nog willen studeren, en dat maakt het kei-hard, want "Alle beetjes helpen" Jezelf kalmeren doe je met deze zin: "2nd shot" Superbekwame instructor. Combineert hard studeren met hard lachen. Goede situatievoorbeelden helpen enorm."
Antonio Vanhove. - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (4/11/2012 t/m 11/11/2012)

"Je heb wel vooraf een fundament van kennis nodig. Het is heel intensief, 13 uur per dag 13 dagen lang. De trainer was uitstekend."
Anoniem - Microsoft MCSA: Windows Server 2008 & MCITP Enterprise Administrator (13 Dagen) (9/9/2012 t/m 21/9/2012)

"Its hardwork and long days but you will be prepared for the exam. This way learning is an experience."
René Beije. - Microsoft MCSA: Windows Server 2008 & MCITP Enterprise Administrator (13 Dagen) (8/7/2012 t/m 20/7/2012)

"Resultaten behaal je door zelf te ondernemen en kansen te pakken. Ervoor gaan betekent inspannen tot het uiterste. Niet wegschrikken voor zeven dagen intensief studeren. Mij ligt dit concept goed. Ik hou ervan om in korte tijd resultaat te zien in plaats van een jaar te moeten doen over een cursus en daar wekelijks mijn tijd voor vrij te maken."
Tristan Jager. - Microsoft MCSA: Windows Server 2008 & MCITP Enterprise Administrator (13 Dagen) (8/7/2012 t/m 20/7/2012)

"Perfecte training, perfecte docent, perfecte locatie in de benelux. Vriendelijke medewerkers. Veel studie, maar dat is ook de bedoeling :)"
Jesper Plass, Ploegam BV. - Microsoft MCSA: Windows Server 2008 & MCITP Enterprise Administrator (13 Dagen) (8/7/2012 t/m 20/7/2012)

"Training is voor doorzetters, heeft een strakke planning en zit vol met tip & trucs om te dealen met de Microsoft examens. Als je nog geen ervaring hebt met een bootcamp, kun je hier alles ervaren ..."
Jan Blom, ICT First. - Microsoft MCSA: Windows Server 2008 (8 Dagen) (8/7/2012 t/m 15/7/2012)

"Uitstekend concept en zeer goede trainer, maar héél zwaar!"
Robert Kriekaard, KBS Bedrijfsondersteuning. - Microsoft MCSA: Windows Server 2008 (8 Dagen) (8/7/2012 t/m 15/7/2012)

"Ik heb nog nooit iemand zien met zo veel kennis van Microsoft (en dat is nog niet eens het enigewaar in hij les geeft). De manier van les geven is heel goed. Beste instructeur ooit! In 7 dagen tijd meer geleerd dan 1 jaar op school."
Freddy Jeurissen, nvt. - Microsoft MCSA: Windows Server 2008 & MCITP Enterprise Administrator (13 Dagen) (8/7/2012 t/m 20/7/2012)

"De intensieve training, maakt het een bijzondere en zeer leerzame ervaring. Door alle tijd die je in een dag kunt krijgen met een onderwerp bezig te zijn is de kennisoverdracht enorm. Zeer ervaren trainer die de lesstof perfect beheerst en kan aanvullen met praktijk ervaring en daarnaast ook zeer aangenaam mens is maakt de ervaring onvergetelijk."
Pieter Borst. - Microsoft MCTS / MCPD SharePoint 2010 Developer (7 Dagen) (10/10/2011 t/m 16/10/2011)

"Voor het eerst heb ik een cursus mogen volgen. Gelukkig voor mij is dit gebeurd onder de Firebrand vlag. 7 zeer intensieve dagen met aan het eind het gevoel dat je echt iets geleerd hebt. De instructeur heeft veel moeite gestopt in het aantrekkelijk maken van de slides + persoonlijke aanpassingen hierdoor is de ervaring uitermate positief."
Ronald van Meer. - Microsoft MCTS / MCPD SharePoint 2010 Developer (7 Dagen) (10/10/2011 t/m 16/10/2011)

"We had Phil Anderson, a very nice and intelligent man. He had to put through a lot of information. I did not take the exam at the end of the week, because I am a person who needs more time to process information. The course was structured and well done by Phil. I would recommend him as a trainer. Teacher gets a 9. The facilities of the training were good. Everything was prepared before the training, so it had an easy start. "
Danny van Oijen, Havenziekenhuis. - Microsoft MCSA: Windows 10 (6 Dagen) (13/3/2017 t/m 18/3/2017)

"Intense study with a great instructor and awesome co-students."
Martin Petersen, Silvaco A/S. - Microsoft MTA Networking, Security & Windows Server Administration (6 Dagen) (25/1/2016 t/m 30/1/2016)

"Fast and Furious but great content delivered by a great instructor. Accelerated Learning can be challenging but 3 certificates in a week speaks for itself. I can go back to work and apply lots of the things I have learned straightaway. Training centre and environment were great, created a nice learning environment and the camaraderie between course members was great."
Sam Hanson, Ace Container Services. - Microsoft MTA Networking, Security & Windows Server Administration (6 Dagen) (25/1/2016 t/m 30/1/2016)

"I thought it would be almost impossible to become SQL Server MCSA in 9 days, its normally 3 weeks of courses plus 3 exam days, but after very hard work I succeeded. Thanks a lot Firebrand and the instructor for that!"
Joakim Ronnberg, Council of the European Union. - Microsoft MCSA: SQL Server (9 Dagen) (13/10/2014 t/m 21/10/2014)

"Firebrand : The fastest way to learn. Great team and very helpful."
Anoniem - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (9/6/2013 t/m 16/6/2013)

"Great teacher, extremely skilled, great personality. "
Steven Pringels , Syncrogenics. - Microsoft Dynamics AX 2012 Development - Advanced (4 Dagen) (15/12/2011 t/m 18/12/2011)

"Great course with a brilliant course teacher. The instructor managed to dumb down complex concepts and made an interactive educative environment."
Mohammad B, CRMCS Consultancy. - Microsoft Specialist: Programming in C# (4 Dagen) (3/7/2017 t/m 6/7/2017)

"The training is very good. It is not passive, so you have to work hard, but you get all the key information you need to build upon - with your own reading and revision adding the extra insight needed for the exam. My expectation before the course was that I might pass one of the three exams, but I soon realised that if I was prepared to work in the evenings as the instructor encouraged us all to, then I could get through them all (so far Ive passed 2 with one more this afternoon!). It was up to me now. Having passed an MCP in server 2003 through self-study - which took nearly 12 months - I was very impressed with how much you can learn when able to get the answers you need from a subject matter expert and how quickly you can get through a single exam - a matter of a few days. The labs were also very useful for getting hands-on experience and testing out what you had learned during the day. In terms of the accommodation and food, it was excellent - a small issue with my shower was fixed within hours and the staff are all friendly and very professional. You get a very good choice of food and if you prefer a low carb diet like myself then thats no problem. If you prefer to relax in the evening then there is a decent bar where you can take some time out with your new friends. "
Ben Kane, Euro Recycling. - Microsoft MCSA: Windows Server 2016 (11 Dagen) (24/6/2017 t/m 4/7/2017)

"Excellent learning environment, knowledgeable staff. Well paced course syllabus."
Matthew Ottley, Manuli Hydraulics UK Ltd. - Microsoft MCSA: Windows Server 2016 (11 Dagen) (24/6/2017 t/m 4/7/2017)

"5th Course at firebrand, and as always a great experience. Trainers are friendly and willing to answer most any questions you may have, even if they have to get back to you later 10/10"
Ethan ODonnell. - Microsoft Windows Server 2016 - Networking (3 Dagen) (28/6/2017 t/m 30/6/2017)

"Very happy with the course and cannot wait to come back for mtadev in a couple of months. Definitely enjoy server work."
Jamie H., Watchfinder&co. - Microsoft MCSA: Windows Server 2016 (11 Dagen) (24/6/2017 t/m 4/7/2017)

"Have been to Firebrand several times and the training is of a high standard. Great way to get qualified in a short time."
Richard Smith, Redcare (5G Communications). - Microsoft MCSA: Windows Server 2012 R2 (9 Dagen) (13/5/2017 t/m 21/5/2017)

"If you are prepared to attend an intense training course, Firebrand is for you. After 3 days of training, I gained a huge amount of knowledge. Just be ready to learn! And take your skills to the next level."
Mark Cunningham, Capgemini. - Microsoft Specialist: Dynamics CRM 2016 Customisation and Configuration (4 Dagen) (16/5/2017 t/m 19/5/2017)

"Firebrand provides great training with brilliant instructors. The course was enjoyable and the resources I had access to were fantastic"
Azimuth Jenkins, Capgemini. - Microsoft Specialist: Dynamics CRM 2016 Customisation and Configuration (4 Dagen) (16/5/2017 t/m 19/5/2017)

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 Lecuture | 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).

Lees meer ...

Belangstelling? Zie onze prijzen of bel ons op 024-8457770

Gebruik de Microsoft vouchers voor gratis opleidingen

De Software Assurance Training Vouchers (SATV) van Microsoft geven u misschien wel recht op een opleiding met flinke korting. Heeft uw onderneming software van Microsoft gekocht? Kijk dan of het gebundeld kan worden met de vouchers voor gratis opleiding! Vouchers kunnen ingewisseld worden voor opleidingen voor alle Microsoft technologieën. Weet u niet zeker of dit voor u geldt, neem dan contact met ons op.De Software Assurance Training Vouchers (SATV) van Microsoft geven u misschien wel recht op een opleiding met flinke korting. Heeft uw onderneming software van Microsoft gekocht? Kijk dan of het gebundeld kan worden met de vouchers voor gratis opleiding! Vouchers kunnen ingewisseld worden voor opleidingen voor alle Microsoft technologieën. Weet u niet zeker of dit voor u geldt, neem dan contact met ons op.

Lees meer ...

Belangstelling? Zie onze prijzen of bel ons op 024-8457770

Analyzing 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, students will 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
  • Summarizing 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, students will be able to:

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

Module 3: Visualizing Big Data

Explain how to visualize data by using graphs and plots.

Lessons

  • Visualizing In-memory data
  • Visualizing big data

Lab : Visualizing data

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

After completing this module, students will be able to:

  • Use ggplot2 to visualize in-memory data
  • Use rxLinePlot and rxHistogram to visualize 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, students will be able to:

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

Module 5: Parallelizing 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 parallelize operations

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

After completing this module, students will be able to:

  • Use the rxLocalParallel compute context with rxExec
  • Use the RevoPemaR package to write customized 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, students will 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, students will 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, students will be able to:

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

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, students will 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, students will 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, students will 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, students will be able to:

  • Pre-process data to clean and normalize 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, students will 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, students will 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, students will 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 visualization using R/Python
  • R programming to work on a time series

After completing this module, students will 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: Initializing and Optimizing 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 : Initializing and optimizing machine learning models

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

After completing this module, students will 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, students will 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, students will 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, students will 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 visualize data

After completing this module, students will 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 - currently in beta

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 - currently in beta

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
  • Operationalize and Manage Azure Machine Learning Services
  • Use Other Services for Machine Learning

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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

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