Artificial Intelligence with Big Data - Data Science Course

3 Days

Overview

In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data.

With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems.

By the end of this course, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems.

What You Will Learn

• Manage Artificial Intelligence techniques for big data with Java

• Build smart systems to analyze data for enhanced customer experience

• Learn to use Artificial Intelligence frameworks for big data

• Understand complex problems with algorithms and Neuro-Fuzzy systems

• Design stratagems to leverage data using Machine Learning process

• Apply Deep Learning techniques to prepare data for modeling

• Construct models that learn from data using open source tools

• Analyze big data problems using scalable Machine Learning algorithms

Table of Contents

1: Big Data and Artificial Intelligence Systems

• Results pyramid

• What the human brain does best

• What the electronic brain does best

• Best of both worlds

• Summary

2: Ontology for Big Data

• Human brain and Ontology

• Ontology of information science

• Summary

3: Learning from Big Data

• Supervised and unsupervised machine learning

• The Spark programming model

• The Spark MLlib library

• Regression analysis

• Data clustering

• The K-means algorithm

• Data dimensionality reduction

• Singular value decomposition

• The principal component analysis method

• Content-based recommendation systems

• Frequently asked questions

• Summary

4: Neural Network for Big Data

• Fundamentals of neural networks and artificial neural networks

• Perceptron and linear models

• Nonlinearities model

• Feed-forward neural networks

• Gradient descent and backpropagation

• Overfitting

• Recurrent neural networks

• Frequently asked questions

• Summary

5: Deep Big Data Analytics

• Deep learning basics and the building blocks

• Building data preparation pipelines

• Practical approach to implementing neural net architectures

• Hyperparameter tuning

• Distributed computing

• Distributed deep learning

• Frequently asked questions

• Summary

6: Natural Language Processing

• Natural language processing basics

• Text preprocessing

• Feature extraction

• Applying NLP techniques

• Implementing sentiment analysis

• Frequently asked questions

• Summary

7: Fuzzy Systems

• Fuzzy logic fundamentals

• ANFIS network

• Fuzzy C-means clustering

• NEFCLASS

• Frequently asked questions

• Summary

8: Genetic Programming

• Genetic algorithms structure

• KEEL framework

• Encog machine learning framework

• Introduction to the Weka framework

• Attribute search with genetic algorithms in Weka

• Frequently asked questions

• Summary

9: Swarm Intelligence

• Swarm intelligence

• The particle swarm optimization model

• Ant colony optimization model

• MASON Library

• Opt4J library

• Applications in big data analytics

• Handling dynamical data

• Multi-objective optimization

• Frequently asked questions

• Summary

10: Reinforcement Learning

• Reinforcement learning algorithms concept

• Reinforcement learning techniques

• Deep reinforcement learning

• Frequently asked questions

• Summary

11: Cyber Security

• Big Data for critical infrastructure protection

• Understanding stream processing

• Cyber security attack types

• Understanding SIEM

• Splunk

• ArcSight ESM

• Frequently asked questions

• Summary

12: Cognitive Computing

• Cognitive science

• Cognitive Systems

• Application in Big Data analytics

• Cognitive intelligence as a service

• Frequently asked questions

• Summary

Acumen Envision run Technical IT courses that are engaging, creative and with content that sticks.

Super Creative

We don't believe in traditional & acceptable We do believe in Creative, Engaging & Sticky. People are not the same, the way they learn is not the same so a program has to engage all mindsets. We use a complex mix of engaging tools combined first class classroom delivery, and continuous measurement to ensure we produce true mindset and behavioural change.

Skilled Instructors

Without our highly skilled training team all of the pre-course consultancy and technology customisation would just not work. The wealth of experience and real world scenarios that they bring to each classroom module enhances the discussion, engagement and overall delivery. So, whether your people are attending a 1-1 Group or Public Technology program they will receive top level classroom tuition as part of their overall learning experience.

Acumen Envision the Transformation Specialists

Specialist Technical IT Training, Sticky Effective Disruptive, We Deliver First Class Results.

Data Science Training for Data Scientists, Data Analysts, Software Developers or Anyone working in a role or wanting to work with large data sets.

Our Data Science courses cover Data Visualization, Python, Jupyter, R, AI, Machine Learning, Data Wrangling, Excel VBA, Access VBA, Scala, Spark, Power BI, Tableau and much more.

Courses run for Data People by Data Specialists.

What’s Included:

• The latest Data Science course content

• Trainers who enjoy Data Science, delivering courses and talking about real word examples.

• Detailed course work book to take away

• Our Extras Pack for post course learning

• Certificate of completion

• Unlimited Refreshments

Why our content sticks.

• We take time to know our participants with pre course evaluation

• We don’t run large class sizes

• Our courses are delivered by subject matter experts who make the content engaging

• We like Hands on, so you can absorb the theory with practice

• We provide a 1-hour WebEx follow up to see how you are getting on to give any additional advice

Want something different?

• Can I have a course on my own. Yes, you can we can provide a 1:1 course for you either on-site or in centre.

• 1-1 or Group Training for your business, no problem.

We can customise content, combine courses or develop a program around your team or specific need.

• Need us to look at something specific, in a black hole with Excel / Access or need to migrate large amounts of data then please contact us to discuss in more detail. Our training are experts in their own field and spend 40% of their time providing on / off site consultancy.

What happens after I book?

• You will get a booking confirmation once you have placed your order.

• If you are booking a course over a weekend don’t worry one of our team will contact you via email on Monday to double check the details with you and check to see if you would like to book an optional lunch.

• We will send you the link to down load all of the tools and software needed for your course.

• 7 Days before your course date we send a reminder

• The morning of the course the course lecturer will greet you in reception if 1:1 course or in the training room if a group course.

• If you need help with anything don’t panic simply call or email us and we will assist.

Our list of Data Science Courses

• Applied Data Science with Python & Jupyter

• Applied Data Visualization with R and ggplot2

• Artificial Intelligence with Big Data

• Big Data Analysing with Python

• Big Data Processing with Apache Spark

• Data Science for Marketing Analytics

• Data Science Projects with Python

• Data Virtualisation with Python

• Data Wrangling with Python

• Excel – Introduction

• Excel – Advanced

• Excel for Data Analysis with Power Pivot

• Excel – Forecasting Data

• Excel – Sparkline and Mapping Data

• Excel – Visualising Data with Charts

• Excel - Dashboards

• Excel VBA Programming

• Access VBA

• VBA Programming

• Microsoft Power BI Data Analysis Professional

• Microsoft Power BI Data Analysis Practitioner

• Scala and Spark with Big Data Analytics

• Python Programming Introduction

• Python Advanced Programming

• Python API Development

• Python Microservices Development

• Machine Learning with Python

• Applied Unsupervised Learning with Python Libraries

• SQL for Data Analytics

• SQL Query Fundamentals

• Tableau Introduction

• Tableau Advanced

Refund Policy

We will provide a refund for all cancellations received 14 days prior to the event.

We accept name changes up to 3 days before the event at no additional cost , if you are unable to attend.

If for any reason we have to cancel the event we will offer you the option to move onto the next available date, attend an alternative course or we will provide a full refund.

Please note that we are not liable for any travel or accommodation costs relating to your course booking.

We always try to help and be as fair as possible, so please contact us at your earliest convenience if you are unable to attend a course you have booked, so we can look at the options available for you.