Machine Learning for Banking (with R) Training Course

Course Code

mlbankingr

Duration

28 hours (usually 4 days including breaks)

Requirements

  • Programming experience with any language
  • Basic familiarity with statistics and linear algebra

Overview

In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the banking industry. R will be used as the programming language.

Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of live projects.

Audience

  • Developers
  • Data scientists
  • Banking professionals with a technical background

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Course Outline

Introduction

  • Difference between statistical learning (statistical analysis) and machine learning
  • Adoption of machine learning technology by finance and banking companies

Different Types of Machine Learning

  • Supervised learning vs unsupervised learning
  • Iteration and evaluation
  • Bias-variance trade-off
  • Combining supervised and unsupervised learning (semi-supervised learning)

Machine Learning Languages and Toolsets

  • Open source vs proprietary systems and software
  • R vs Python vs Matlab
  • Libraries and frameworks

Machine Learning Case Studies

  • Consumer data and big data
  • Assessing risk in consumer and business lending
  • Improving customer service through sentiment analysis
  • Detecting identity fraud, billing fraud and money laundering

Introduction to R

  • Installing the RStudio IDE
  • Loading R packages
  • Data structures
  • Vectors
  • Factors
  • Lists
  • Data Frames
  • Matrixes and Arrays

How to Load Machine Learning Data

  • Databases, data warehouses and streaming data
  • Distributed storage and processing with Hadoop and Spark
  • Importing data from a database
  • Importing data from Excel and CSV

Modeling Business Decisions with Supervised Learning

  • Classifying your data (classification)
  • Using regression analysis to predict outcome
  • Choosing from available machine learning algorithms
  • Understanding decision tree algorithms
  • Understanding random forest algorithms
  • Model evaluation
  • Exercise

Regression Analysis

  • Linear regression
  • Generalizations and Nonlinearity
  • Exercise

Classification

  • Bayesian refresher
  • Naive Bayes
  • Logistic regression
  • K-Nearest neighbors
  • Exercise

Hands-on: Building an Estimation Model

  • Assessing lending risk based on customer type and history

Evaluating the performance of Machine Learning Algorithms

  • Cross-validation and resampling
  • Bootstrap aggregation (bagging)
  • Exercise

Modeling Business Decisions with Unsupervised Learning

  • When sample data sets are not available
  • K-means clustering
  • Challenges of unsupervised learning
  • Beyond K-means
  • Bayes networks and Markov Hidden Models
  • Exercise

Hands-on: Building a Recommendation System

  • Analyzing past customer behavior to improve new service offerings

Extending your company's capabilities

  • Developing models in the cloud
  • Accelerating machine learning with additional GPUs
  • Applying Deep Learning neural networks for computer vision, voice recognition and text analysis

Closing Remarks

Testimonials

★★★★★
★★★★★

Bookings, Prices and Enquiries

Guaranteed to run even with a single delegate!

Private Classroom

From £5800

Private Remote

From £5200 (94)

Public Classroom

Location Date Course Price [Remote/Classroom]
Exeter - The Senate2018-10-30 09:30£ 5200 / £ 6400
Reading TVP2018-11-05 09:30£ 5200 / £ 6260
Newcastle2018-11-05 09:30£ 5200 / £ 6000
Leeds2018-11-05 09:30£ 5200 / £ 6600
Birmingham 2018-11-05 09:30£ 5200 / £ 6500
Liverpool2018-11-06 09:30£ 5200 / £ 6600
Southampton2018-11-06 09:30£ 5200 / £ 6200
Swindon2018-11-06 09:30£ 5200 / £ 5900
Belfast City Centre2018-11-12 09:30£ 5200 / £ 7000
Coventry - The Quadrant2018-11-12 09:30£ 5200 / £ 6200
London, Hatton Garden2018-11-19 09:30£ 5200 / £ 6700
Brighton2018-12-03 09:30£ 5200 / £ 6000
St Helier, Jersey, Channel Isles2018-12-03 09:30£ 5200 / £ 7100
Manchester, King Street2018-12-04 09:30£ 5200 / £ 6500
Portsmouth2018-12-10 09:30£ 5200 / £ 5800
Oxford2018-12-10 09:30£ 5200 / £ 6300
Aberdeen - Berry Street2018-12-10 09:30£ 5200 / £ 6520
Edinburgh Training and Conference Venue2018-12-10 09:30£ 5200 / £ 6000
Glasgow2018-12-11 09:30£ 5200 / £ 6600
Bristol, Temple Gate2018-12-11 09:30£ 5200 / £ 6200
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Course Discounts

Course Venue Course Date Course Price [Remote / Classroom]
Jenkins: Continuous Integration for Agile Development Manchester, King Street Thu, 2018-10-18 09:30 £2574 / £3224
Introduction to Recommendation Systems Swansea- Princess House Thu, 2018-10-18 09:30 £990 / £1140
Advanced Statistics using SPSS Predictive Analytics Software Birmingham Mon, 2018-10-22 09:30 £5148 / £6448
Building Augmented Reality Applications with Vuforia and Unity Glasgow Wed, 2018-10-24 09:30 £2178 / £2878
Impact Evaluation – Quantitative Analysis London, Hatton Garden Wed, 2018-10-24 09:30 £2574 / £3324
Statistics with SPSS Predictive Analytics Software Cambridge Thu, 2018-11-01 09:30 £2574 / £3024
Programming in Scala Cambridge Thu, 2018-11-01 09:30 £2178 / £2628
CakePHP: Rapid Web Application Development Birmingham Tue, 2018-11-06 09:30 £4356 / £5656
AWS: A Hands-on Introduction to Cloud Computing Brighton Wed, 2018-11-07 09:30 £1287 / £1487
JMeter Fundamentals and JMeter Advanced Edinburgh Training and Conference Venue Mon, 2018-12-03 09:30 £2178 / £2578
HAProxy Administration London, Hatton Garden Mon, 2018-12-03 09:30 £2178 / £2928
Social Media Marketing Oxford Wed, 2018-12-12 09:30 N/A / £1364
Test Automation with Selenium Manchester, King Street Wed, 2018-12-12 09:30 £3267 / £4242

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