Certificate In Machine Learning with Python Online Course

Linear Algebra, Natural Language and more

Certificate In Machine Learning with Python Online Course

NOW ONLY

US$99

Save US$500 (83%)
OFF RRP US$599
Get Info Pack

Linear Algebra, Natural Language and more

If you’re plugged into the tech industry, you’ll know that two things have been making consistent waves in many areas over the past few years; machine learning and Python. What happens when you combine the new gold standard programming language with the most significant tech development in areas such as financial trading, online search, digital marketing and even data and personal security (among others)? Great things, that’s what. This course will show you what’s what, and get you started on becoming a machine learning guru.

Learn the New Future of Programming

  • Understand what machine learning is and what it can do
  • Discover how Python utilises machine learning
  • Build machine learning processing from the ground up
  • Delve into complex logic and data structures

Increase Your Python Expertise

If you have a desire to learn machine learning concepts and have some previous programming or Python experience, this course is perfect for you. If you’re more of a beginner than an intermediate, don’t worry; each module starts with theory to explain upcoming concepts. Once you’re comfortable, you’ll put your knowledge into practice with a code walk through.

The goal of this course is to build procedural machine learning from the ground up. Writing processing from scratch allows students to gain a more in-depth insight into data processing, and as each machine learning app is created, explanations and comments are provided to help students understand why things are being done in certain ways. Each code walk through also shows the building process in real time.

The course begins with an introduction to machine learning concepts, after which you’ll build your first machine learning application. Following that, we look at data analysis, linear algebra, natural language processing and clustering, all within the context of Python. At the end of the course, you’ll be issued with a certificate of completion and will have gained a full introduction into the world of machine learning with Python.

What is Machine Learning?

Machine learning is a method of data analysis that essentially allows computers to ‘learn’ on their own without being explicitly programmed. For example, when you stop scrolling through Facebook to read a friend or a page’s post, algorithms automatically work to make sure you’ll see more content from those sources earlier in your news feed in future.

Course Fast Facts:

  1. Learn the fundamentals of Machine Learning with Python
  2. Comprehensive 7 module Accredited Certificate In Machine Learning with Python Online Course
  3. Study along with simple instructions & demonstrations
  4. Written and developed by leading Python experts
  5. Receive one-on-one online help & support
  6. Unlimited, lifetime access to online course
  7. Certificate of completion
  8. Study at your own pace with no rigid class timetables, 24/7 from any computer or smart device

Course Delivery

Courses are accessed online  by any device including PC, tablet or Smart Phone. Upon purchase an automated welcome email will be sent to you (please check your junk email inbox if not received as this is an automated email), in order for you to access your online course, which is Available 24/7 on any computer or smart mobile device. 

Recognition & Accreditation

All students who complete this course, receive a certificate of completion and will be issued a certificate via email.

Course Introduction

  • Course Introduction

Machine Learning Concepts

  • Section Introduction
  • Supervised and Unsupervised Learning
  • Semi-Supervised Learning
  • Section Summary

First ML Application

  • Section Introduction
  • Installing the Environment
  • Hello World
  • Installing Aaconda and Deep Learning Libraries
  • Email Spam Checker - Part 1
  • Email Spam Checker - Part 2
  • Email Spam Checker Results
  • Iris 70:30 - Part 1
  • Iris 70:30 - Part 2
  • Section Summary

Data Analysis

  • Section Introduction
  • Data Analysis - Example 1
  • Data Analysis - Example 2
  • Data Visualization
  • Section Summary

Linear Algebra

  • Section Introduction
  • Parametric Algorithms
  • Linear Algebra
  • Linear Regression Calculation - Part 1
  • Linear Regression Calculation - Part 2
  • Regression on Larger Dataset - Part 1
  • Regression on Larger Dataset - Part 2
  • Regression on Larger Dataset - Part 3
  • Section Summary

Natural Language Processing

  • Section Introduction
  • Natural Language Processing - Part 1
  • Natural Language Processing - Part 2
  • Tokenizing Content
  • Processing Unique Words
  • Summarizing Headlines - Part 1
  • Summarizing Headlines - Part 2
  • Summarizing Headlines - Part 3
  • Section Summary

Clustering

  • Section Introduction
  • Cluster Introduction
  • EM and M Clustering
  • Clustering Code Walkthrough
  • Clustering Iris Data - Part 1
  • Clustering Iris Data - Part 2
  • Clustering Iris Data - Part 3
  • Dendrogram Graphs
  • Section Summary
  • Course Summary

Entry requirements

Students must have basic literacy and numeracy skills.

Minimum education

Open entry. Previous schooling and academic achievements are not required for entry into this course.

Computer requirements

Students will need access to a computer and the internet. 

Minimum specifications for the computer are:

Windows:

  • Microsoft Windows XP, or later
  • Modern and up to date Browser (Internet Explorer 8 or later, Firefox, Chrome, Safari)

MAC/iOS

  • OSX/iOS 6 or later
  • Modern and up to date Browser (Firefox, Chrome, Safari)

All systems

  • Internet bandwidth of 1Mb or faster
  • Flash player or a browser with HTML5 video capabilities(Currently Internet Explorer 9, Firefox, Chrome, Safari)

Students will also need access the following applications:

Adobe Acrobat Reader

About this Course

Linear Algebra, Natural Language and more

If you’re plugged into the tech industry, you’ll know that two things have been making consistent waves in many areas over the past few years; machine learning and Python. What happens when you combine the new gold standard programming language with the most significant tech development in areas such as financial trading, online search, digital marketing and even data and personal security (among others)? Great things, that’s what. This course will show you what’s what, and get you started on becoming a machine learning guru.

Learn the New Future of Programming

  • Understand what machine learning is and what it can do
  • Discover how Python utilises machine learning
  • Build machine learning processing from the ground up
  • Delve into complex logic and data structures

Increase Your Python Expertise

If you have a desire to learn machine learning concepts and have some previous programming or Python experience, this course is perfect for you. If you’re more of a beginner than an intermediate, don’t worry; each module starts with theory to explain upcoming concepts. Once you’re comfortable, you’ll put your knowledge into practice with a code walk through.

The goal of this course is to build procedural machine learning from the ground up. Writing processing from scratch allows students to gain a more in-depth insight into data processing, and as each machine learning app is created, explanations and comments are provided to help students understand why things are being done in certain ways. Each code walk through also shows the building process in real time.

The course begins with an introduction to machine learning concepts, after which you’ll build your first machine learning application. Following that, we look at data analysis, linear algebra, natural language processing and clustering, all within the context of Python. At the end of the course, you’ll be issued with a certificate of completion and will have gained a full introduction into the world of machine learning with Python.

What is Machine Learning?

Machine learning is a method of data analysis that essentially allows computers to ‘learn’ on their own without being explicitly programmed. For example, when you stop scrolling through Facebook to read a friend or a page’s post, algorithms automatically work to make sure you’ll see more content from those sources earlier in your news feed in future.

Course Fast Facts:

  1. Learn the fundamentals of Machine Learning with Python
  2. Comprehensive 7 module Accredited Certificate In Machine Learning with Python Online Course
  3. Study along with simple instructions & demonstrations
  4. Written and developed by leading Python experts
  5. Receive one-on-one online help & support
  6. Unlimited, lifetime access to online course
  7. Certificate of completion
  8. Study at your own pace with no rigid class timetables, 24/7 from any computer or smart device

Course Delivery

Courses are accessed online  by any device including PC, tablet or Smart Phone. Upon purchase an automated welcome email will be sent to you (please check your junk email inbox if not received as this is an automated email), in order for you to access your online course, which is Available 24/7 on any computer or smart mobile device. 

Recognition & Accreditation

All students who complete this course, receive a certificate of completion and will be issued a certificate via email.

Course Introduction

  • Course Introduction

Machine Learning Concepts

  • Section Introduction
  • Supervised and Unsupervised Learning
  • Semi-Supervised Learning
  • Section Summary

First ML Application

  • Section Introduction
  • Installing the Environment
  • Hello World
  • Installing Aaconda and Deep Learning Libraries
  • Email Spam Checker - Part 1
  • Email Spam Checker - Part 2
  • Email Spam Checker Results
  • Iris 70:30 - Part 1
  • Iris 70:30 - Part 2
  • Section Summary

Data Analysis

  • Section Introduction
  • Data Analysis - Example 1
  • Data Analysis - Example 2
  • Data Visualization
  • Section Summary

Linear Algebra

  • Section Introduction
  • Parametric Algorithms
  • Linear Algebra
  • Linear Regression Calculation - Part 1
  • Linear Regression Calculation - Part 2
  • Regression on Larger Dataset - Part 1
  • Regression on Larger Dataset - Part 2
  • Regression on Larger Dataset - Part 3
  • Section Summary

Natural Language Processing

  • Section Introduction
  • Natural Language Processing - Part 1
  • Natural Language Processing - Part 2
  • Tokenizing Content
  • Processing Unique Words
  • Summarizing Headlines - Part 1
  • Summarizing Headlines - Part 2
  • Summarizing Headlines - Part 3
  • Section Summary

Clustering

  • Section Introduction
  • Cluster Introduction
  • EM and M Clustering
  • Clustering Code Walkthrough
  • Clustering Iris Data - Part 1
  • Clustering Iris Data - Part 2
  • Clustering Iris Data - Part 3
  • Dendrogram Graphs
  • Section Summary
  • Course Summary

Entry requirements

Students must have basic literacy and numeracy skills.

Minimum education

Open entry. Previous schooling and academic achievements are not required for entry into this course.

Computer requirements

Students will need access to a computer and the internet. 

Minimum specifications for the computer are:

Windows:

  • Microsoft Windows XP, or later
  • Modern and up to date Browser (Internet Explorer 8 or later, Firefox, Chrome, Safari)

MAC/iOS

  • OSX/iOS 6 or later
  • Modern and up to date Browser (Firefox, Chrome, Safari)

All systems

  • Internet bandwidth of 1Mb or faster
  • Flash player or a browser with HTML5 video capabilities(Currently Internet Explorer 9, Firefox, Chrome, Safari)

Students will also need access the following applications:

Adobe Acrobat Reader

We provide a 7 Day Money Back Refund on all Courses

Now Only US$99 Save US$500 (83%)
OFF RRP US$599
Delivery Method Online
Get Info Pack

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Course Summary

Course ID No.: 009SRMLWP
Delivery Mode: Online
Course Access: Unlimited lifetime
Tutor Support: Yes
Time required: Study at your own pace
Course Duration: 5 Hours
Assessments: Yes
Qualification: Certificate

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