Udemy

Platform

English

Language

Data Science

Category

Intro to Big Data, Data Science and Artificial Intelligence

Big Data Technology & Tools for Non-Technical Leaders. Industry expert insights on IoT, AI and Machine Learning for all.

4.29 (667 reviews)

1205

Students

3.5 hours

Content

Jul 2020

Last Update
$39.99
Regular Price


What you will learn

Examples of Big Data and Data Science in Practice (Healthcare, Logistics & Transportation, Manufacturing, and Real Estate & Property Management industries)

Big Data Definition and Data Sources. Why we need to be data and technology savvy.

Introduction to Data Science and Skillset required for working with Big Data

Technological Breakthroughs which Enable Big Data Solutions (Connectivity, Cloud, Open Source, Hadoop and NoSQL)

Big Data Technology Architecture and most popular technology tools used for each Architecture Layer

Beginner's Introduction to Data Analysis, Artificial Intelligence and Machine Learning

Simplified Overview of Machine Learning Algorithms and Neural Networks


Description

If you are like me - finding it difficult to read thick manuals with formulae, but still very much interested in modern technologies and their applications, then this course is for you.

You will learn about big data, Internet of Things (IoT), data science, big data technologies, artificial intelligence (AI), machine learning (ML) algorithms, neural networks, and why this could be relevant to you even if you don't have technology or data science background. Please note that this is NOT TECHNICAL TRAINING and it does NOT teach Coding/Development or Statistics.

The course includes the interviews with industry experts that cover  big data developments in Real Estate, Logistics & Transportation and Healthcare industries.  You will learn how machine learning is used to predict engine failures, how artificial intelligence is used in anti-ageing, cancer treatment and clinical diagnosis, you will find out what technology is used in managing smart buildings and smart cities including Hudson Yards in New York.  We have got fantastic guest speakers who are the experts in their areas:

- WAEL ELRIFAI - Global VP of Solution Engineering - Big Data, IoT & AI at Hitachi Vantara with over 15 years of experience in the field of machine learning and IoT. Wael is also a Co-Authour of the book "The Future of IoT".

- ED GODBER - Healthcare Strategist with over 20 years of experience in Healthcare, Pharmaceuticals and start-ups specialising in Artificial Intelligence.

- YULIA PAK - Real Estate and Portfolio Strategy Consultant with over 12 years of experience in Commercial Real Estate advisory, currently working with clients who deploy IoT technologies to improve management of their real estate portfolio.

Hope you will enjoy the course and let me know  in the comments of each section how I can improve the course!


Screenshots

Intro to Big Data, Data Science and Artificial Intelligence
Intro to Big Data, Data Science and Artificial Intelligence
Intro to Big Data, Data Science and Artificial Intelligence
Intro to Big Data, Data Science and Artificial Intelligence

Content

Course overview and Introduction to big data

Course Introduction

Guest Speakers

BEFORE YOU START

Why learn about big data?

Big data definition and Sources of data

Big Data Definition

Big Data in Practice - LOGISTICS & TRANSPORTATION

Section introduction

Logistics & Transportation: Social Impact of Artificial Intelligence & IoT

Logistics & Transportation: Predictive & Prescriptive Maintenance

Logistics & Transportation: Prepositioning of Goods and Just in Time inventory

Logistics & Transportation: Route Optimisation

Logistics & Transportation: Warehouse Optimisation and order picking

Logistics & Transportation: The Future of the industry

Logistics and Transportation Quiz

Big Data in Practice - PREDICTIVE MAINTENANCE IN MANUFACTURING

Predictive Maintenance in Manufacturing - Case Study SIBUR

Big Data in Practice: REAL ESTATE & PROPERTY MANAGEMENT

Real Estate: Introduction to big data in real estate

Real Estate: Business Drivers for Using Big Data

Real Estate & Property Management: Technological Enablers

Real Estate: Building Asset Management and Building Information Modelling

Real Estate: Big Data and IoT in Building Maintenance and Management - examples

Real Estate: Smart Buildings

Additional Resources to Lecture on Smart Buildings

Real Estate: Smart Cities (examples - Los Angeles and Hudson Yards in New York)

Additional resources on Smart Cities

Real Estate: Smart Technologies Cost and Government Subsidies (example - Norway)

Real Estate: Data Driven Future

Real Estate and Property Management

Big Data in Practice: HEALTHCARE

Healthcare: Data Challenges in Healthcare Industry

Healthcare: Transforming Role of AI and Data Measurement Technologies

Healthcare: Artificial Intelligence in Disease Prevention

Healthcare: Artificial Intelligence in Anti-Ageing

Healthcare: AI in Clinical Decision Making and Cancer Treatment

Healthcare: Clash of AI and Traditional Healthcare Science

Healthcare: Final Remarks - Value of Artificial Intellegence to Consumers

BIG DATA IN PRACTICE: SECTION WRAP-UP

Healthcare

Data Science and Required Skillset

Data Science Definition and Required Skillset

Guest Speakers importance of working in teams & understanding business objective

Data Science Skillset: Section Wrap-Up

Handouts

Data Science Skills

Introduction to Big Data Technologies

Key Technological Advances and Enablers

Wide Adoption of Cloud Computing

Data Management Technological Breakthroughs (e.g. NoSQL, Hadoop)

Open Source and Open APIs

Big Data Enablers

Additional Resources and Handouts

Big Data Technology Architecture (including examples of popular technologies)

Big data technology architecture

Additional Resources and Handouts

Introduction to data analysis, Artificial Intelligence and Machine Learning

Why to be data and tech savvy

Big Data Analytics and Artificial Intelligence Definitions

Machine Learning Workflow and Training a Model

Model Accuracy and Ability to Generalise

Machine Learning Components: DATA

Machine Learning Components: FEATURES

Machine Learning Components: ALGORITHMS

Additional Resources and Handouts

Introduction to AI quiz

Simplified Overview of Machine Learning Algorithms

Classical Machine Learning: Supervised and Unsupervised Learning

SUPERVISED LEARNING: Classification

Classification: Naive Bayes

Classification: Decision Trees

Classification: Support Vector Machines (SVM)

Classification: Logistic Regression

Classification: K Nearest Neighbour

Classification: Anomaly Detection

SUPERVISED LEARNING: Regression

Classical Machine Learning: Unsupervised Learning

UNSUPERVISED LEARNING: Clustering

Clustering: K-Means

Clustering: Mean-Shift

Clustering: DBSCAN

Clustering: Anomaly Detection

UNSUPERVISED LEARNING: Dimensionality Reduction

UNSUPERVISED LEARNING: Association Rule

CLASSICAL MACHINE LEARNING - Section Wrap Up

REINFORCEMENT LEARNING

ENSEMBLES

Machine Learning Quiz

Introduction to Deep Learning and Neural Networks

DEEP LEARNING AND NEURAL NETWORKS

NEURAL NETWORKS: Convolutional Neural Network

NEURAL NETWORKS: Recurrent Neural Network

NEURAL NETWORKS: Generative Adversarial Network (GAN)

Additional Resources

Neural Networks Quiz

Machine Learning Sections Wrap-up

Choosing AI algorithms

Additional Resources and Handouts

Course Wrap up

Your feedback and more resources



Reviews

D
Dian29 September 2020

This course is recommended for more than awareness level on data science and AI . Many new jargon for those who is outside from this field. Maybe can use animation to simplified things during the delivery of the speakers.

M
Mustapha25 September 2020

It combines a balance between an exhaustive 'practical expertise' and 'knowledge domains field integration'. Thank you for your professionalism, Clarity, and value-added by your Guest expert Speakers.

N
Noradnin23 September 2020

-to put summary on the learnings -instead of too many subchapter with 1,2,3 minutes each, I believe some of them can be combine e.g to become 5 or 10 minutes.

A
Ali13 September 2020

I have been looking for a course without any pre-requisites and yet with a non-technical approach for the executives... So far, wonderful...

B
Boon24 August 2020

Easy to understand course. The instructor paced it well and she would displayed keywords extensively throughout the lessons. Good course for beginner.

M
Muhamad14 August 2020

Very good training from experience personnel. I feel the training materials/ handout need to be given for each element. Tqvm

A
Andy12 August 2020

It was a good knowledge on Big Data, Data Science and AI. Will use it for my future reference in my career. Good Job!!!

K
Ku10 August 2020

It is a very good learning modules. Now, i have much better understanding on big data, data science and AI.

N
Nor9 August 2020

after the training then I know there are very significant impact of managing the data in healthcare where can save a lot of life

H
Hasfuan6 August 2020

This is a good introductory course to big data. The content presented will make you aware on what big data is, the structure behind it, the tools / algorithm to get you through every stage of the big data structure and more importantly how you can relate it to industry application. Having the invited speakers to describe big data application to their respective industry is very helpful.

N
Norazliza5 August 2020

A great course indeed! Simple, clear and easy to understand presentation for someone with very limited knowledge on Data Science and Digital world. Indeed is an eye opener on the application of Data Science and AIs in various areas.

Z
Zainol5 August 2020

i love how the learning material is being explain in various different industry. Hopefully one more expert can be added from the O&G/energy industry in the future

S
Sominidevi4 August 2020

This course makes it easier for a beginner to understand the big data concept and applications. The idea of giving real life examples for each section helps to boost the understanding about big data applications in industry.

M
Muis29 July 2020

much have been known. but the depth is appreciated in this short course. the short video module for each topics/sub topic kept it interesting. the slight depth is just enough to increase the deeper knowledge (various common tool and technology today) to understand about big data, data science and AI

A
Andre28 July 2020

Very interesting but long. Maybe this would allow to drill down on specific topics more while on a different level the management aspect could be addressed.



2427676

Udemy ID

6/24/2019

Course created date

12/26/2020

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