This course is part of the Deep Learning and Python Programming for AI with Microsoft Azure ExpertTrack
Deep Learning on Azure with Python: Introduction to Machine Learning
Discover how to become a machine learning engineer in this hands-on introduction to machine learning, using Python programming.
Duration
5 weeksWeekly study
5 hoursIncluded in an ExpertTrack
Course 3 of 5
Deep Learning on Azure with Python: Introduction to Machine Learning
Explore machine learning basics to build more efficient systems
This self-paced course offers you the chance to explore the key skills needed to become a machine learning engineer, in turn developing your understanding of how deep learning works. Machine learning is the process through which artificial intelligence systems use data to become more efficient and effective. No human input is required, beyond the data science skills needed to build machine learning models and set parameters for refinement.
Explore machine learning concepts and applications
The data science insights generated through machine learning are detailed and immediate. The process allows you to build sophisticated and efficient systems, with a huge range of applications. Everything from Netflix recommendations to self-driving cars to medical diagnostic technologies are built around machine learning algorithms.
Unsurprisingly, it is a valuable market: an estimated $7.3 billion in 2020. This is set to rise to $30.6 billion by 2024.
In this introduction to machine learning, you’ll develop the data science skills to build machine learning models using Microsoft Cognitive Services on the Azure cloud platform, and Python programming.
Discover how to become a machine learning engineer
You’ll learn the first steps of how to become a machine learning engineer. You’ll cover practical machine learning skills, with hands-on learning using Python in Microsoft Cognitive Services. With these artificial intelligence skills, you’ll be able to build your own machine learning models, forming the basis of deep learning models, as you develop further data science skills in following courses.
What topics will you cover?
- Introduction to Machine Learning & Knowledge Discovery
- Exploring & Evaluating Data
- Cleaning & Preparing Data
- Getting Started with Supervised Machine Learning
- Improving Machine Learning Model Performance
- Machine Learning Algorithms
- Unsupervised Machine Learning
Prove you're job ready
Highlight the new, job-relevant skills you’ve gained and supplement existing qualifications with a hard-earned, industry-specific digital certificate – plus one for every course within your ExpertTrack.
- Learn the latest in your chosen industry or subject.
- Complete each course and pass assessments.
- Receive certificates validated by the educating organisation.
- Impress employers with learning outcomes you can add to your CV.
- Make your career dreams a reality.
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Learning on this course
You can take this self-guided course and learn at your own pace. On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Explored, prepared and cleaned data
- Applied supervised machine learning techniques
- Applied unsupervised machine learning techniques
- Modeled performance improvement
Who is the course for?
This machine learning and artificial intelligence course is designed for those who would like to learn more about deep learning. Basic knowledge of python programming would be advantageous, as would solid maths and computer science skills.
Who developed the course?
CloudSwyft Global Systems, Inc.
CloudSwyft has partnered with the top global technology companies to deliver cutting edge digital skills learning across the modern workplace.
Learning on FutureLearn
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Join a global classroom
- Experience the power of social learning, and get inspired by an international network of learners
- Share ideas with your peers and course educators on every step of the course
- Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others
Map your progress
- As you work through the course, use notifications and the Progress page to guide your learning
- Whenever you’re ready, mark each step as complete, you’re in control
- Complete 90% of course steps and all of the assessments to earn your certificate
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