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Workshop: Machine Learning – Data Science & Analytics for Developers

November 22, 2017 at 09:00 - November 24, 2017 at 17:00 UTC+1

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Machine Learning – Data Science & Analytics for Developers (Full Course) with Phil Winder

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Please Note This Is a Paid Course And Registrations Must Go Through Link Below or by Contacting Us Directly: https://gotoacademy-co-uk.myshopify.com/products/introduction-to-analytics-and-data-science

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Use the Code “AnalyticsMeetup” to get 15% off when registering

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GOTO Academy are excited to bring you UK-based Phil Winder of Winder Research, for an intensive 3-day Data science and Analytics course, that will leave you with practical tools for utilizing Machine Learning principles in your organisation.

This course combines beginner, intermediate and advanced courses into one efficient program. At the end of this course you will be considered professionally capable of developing and delivering data science products. Immediately start applying what you’ve learnt!

The 3-day course can be reduced to a consecutive 2-day course depending on your skill level and your learning goals. If you’re unsure which package is right for you, please contact us.

WHO WILL BENEFIT 

This course is aimed towards developers, in which we will delve into the mathematics behind the code as well as developing real life algorithms in Python. One-to-one help will be provided for developers new to Python and all algorithms, frameworks and libraries used will be demonstrated by the instructor.

PREREQUISITES

This is a full beginner to advanced level course, which is suitable for most users with some development experience. Some experience of Python is helpful, but not necessary. No data science experience is expected.

If you are a developer with some experience with data science you are welcome to join from Day 2.

COURSE STRUCTURE 

Each day will comprise of a series of sub-hour theoretical sessions separated by practical exercises. The expected learning outcomes for each day are as follows:

WHAT WILL YOU ACHIEVE ON DAY 1 

Discuss the differences between types of learningDescribe problems in a way which can be solved with Data ScienceUnderstand the difference between regression and classificationSolve problems using regression algorithmsSolve problems using classification algorithmsLearn how to avoid overfitting and appreciate generalisationDevelop features within dataDescribe how and where to obtain data

TOPICS COVERED

How data science fits within a business contextData science processes and languageInformation and uncertaintyTypes of learningSegmentationModellingOverfitting and generalisationHoldout and validation techniquesOptimisation and simple data processingLinear regressionClassification and clusteringFeature engineeringAn in-depth practical example demonstrating the day’s concepts

WHAT YOU WILL LEARN ON DAY 2

Evaluate models numericallyInvestigate and assess models visuallyHave practical experience in industrial statisticsFurther enhance data pre-processing skillsUnderstand unsupervised learningGain experience in a wide variety of Machine Learning algorithms

TOPICS COVERED

Numerical and visual model evaluationIntroduction and application of statistics in data scienceUnderstand the practical steps to design and deploy modelsFurther experience with real-life messy dataUnsupervised Machine LearningA range of Machine Learning models: e.g. Logistic regression, linear and nonlinear SVMs, decision trees, etc.Introduction to tooling, testing and deploymentAn in-depth practical example demonstrating the day’s concepts

WHAT WILL YOU ACHIVE ON DAY 3

Develop solutions to mine, analyse and classify textDiscuss and explain neural networks, deep learning and a range of topologiesEmploy semi-supervised machine learning to complex problemsUse ensemble methods to create cutting-edge machine learning products

TOPICS COVERED

Text feature engineeringText mining, representation and learningNeural networksDeep belief networksStacked denoising autoencodersConvolutional neural networksSemi-supervised machine learningEnsemble methodsAn in-depth practical example demonstrating the day’s concepts

TRAINER: PHIL WINDER

Phil Winder is a multi-disciplinary freelance architect working towards the research and development of cutting-edge technology.

Most recently he has been developing cloud-based full-stack microservice systems for a range of clients but has a significant past in machine learning and electronics.

His company, Winder Research has recently released a range of developer and business focused Data Science training courses. Visit WinderResearch.com to find out more.

Phil has PhD and Masters degrees from the University of Hull, UK in Electronics, with a focus on embedded signal processing

DETAILS

Address: London 
Date: 22-24 November, 2017
Duration: 3 days. All days 9:00 to 17:00
Price: 1’600 GBP incl. VAT and meals
Discounts: Group discount 3+: 10%, 6+ 15% Please Contact us for group discounts.
Payment: Card payment online or invoice option.
Registration: Please either “Add to Cart” here on the website or write an email to mto@trifork.com. You will receive an invoice and a confirmation after registering. 

CANCELLATION POLICY

We do not provide any refunds. What happens in case you cannot attend the course?
1) You are welcome to pass on the place to a colleague or
2) You are welcome to attend a later course in our course calendar.
Further, once a registration has been made and the confirmation email has been sent out, the price is set and can not be changed or adjusted.

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Use the Code “AnalyticsMeetup” to get 15% off when registering

——————————————————————————

Please Note This Is a Paid Course And Registrations Must Go Through Link Below or by Contacting Us Directly: https://gotoacademy-co-uk.myshopify.com/products/introduction-to-analytics-and-data-science

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Details

Start:
November 22, 2017 at 09:00
End:
November 24, 2017 at 17:00
Website:
https://www.meetup.com/GOTO-Nights-London-UK

Venue

10 South Place EC2M 2RB London, gb