Deep Learning and Python Programming for AI with Microsoft Azure
Discover deep learning in Azure in this ExpertTrack covering AI fundamentals, machine learning, and deep learning with Python.
Duration
Approx 21 weeks5-6 hrs per week
Get an introduction to deep learning to boost your career in AI
Created in collaboration with Microsoft, this ExpertTrack offers advanced training in artificial intelligence and deep learning for AI professionals, students, analysts and engineers looking to take their AI skills and career to a higher level.
Through online lectures and hands-on lab environments using software powered by CloudSwyft and Azure, you’ll build the skills to sit and pass the Microsoft Azure AI Engineer Associate Exam (AI-100). The cost of this course includes a voucher to sit this Microsoft certification exam online.
Get advanced training in using Microsoft Azure for AI
While 77% of us already use an AI-powered service, artificial intelligence is set to define the next generation of software solutions. PwC predicts AI, robotics, and smart automation will contribute up to 15 trillion dollars to global GDP by 2030.
Using the Microsoft Azure cloud infrastructure, you’ll grow your knowledge of the latest AI programming solutions, covering everything from speech recognition to natural language processing.
Gain a professional certificate in deep learning
This ExpertTrack will teach you how to build and implement cutting-edge AI technology that enables deep learning.
You’ll learn how to apply machine learning to build predictive models for AI and identify the core concepts that underpin deep learning.
You’ll then explore how software can be used to process, analyse, and extract meaning from natural language, as well as process images and video – enabling it to understand the world the way humans do.
Explore key concepts in machine learning and AI
As you examine examples of AI applications in the real-world, you’ll develop your understanding of the technology behind key AI systems and learn how to use and apply this technology yourself using Azure.
You’ll also discover how to build intelligent bots that enable conversational communication between humans and AI systems, as well as design deep semantic similarity models (DSSM) and neural models for machine translations. You’ll then build basic signal processing for speech recognition, acoustic modelling, labelling and common algorithms for language modelling.
Learn with AI training and teaching experts
This certificate course is a collaboration between Microsoft, CloudSwyft, and FutureLearn.
Rich in self-paced content modules, lectures, and unique live hands-on lab environments, you’ll be learning from those paving the way for millions looking to build future-proof technology skills for the modern jobs market.
Industry statistics
Median base salary
£45,000UK job openings/month
1,724
Key skills you will learn
- Artificial Inteligence
- Machine learning
- Deep learning
- Python programming
- Microsoft Azure
- Data science
- Data analysis
- Statistics and probability
- Python data structures
- Statistical Modelling
- Neural networks
Experience required
There are no formal entry requirements for this deep learning ExpertTrack. It is designed to be an introduction to deep learning, teaching you AI, machine learning, and Python fundamentals.
You will be working with intermediate level data science, however, so you will need strong mathematical, statistical, and computer science skills. A basic grasp of Python programming would also be advantageous.
Getting started
This deep learning ExpertTrack addresses skills gaps in the AI and deep learning sector. It will enhance your employability in the artificial intelligence, analytics, data science, and machine learning industries.
It would suit anyone looking to build understanding and skills in machine/deep learning: current or aspiring AI and IT professionals, data analysts, software developers, cloud specialists, applied mathematics and statistics experts, data scientists, chatbot developers, AI engineers, or data researchers. This ExpertTrack can also help you transition into machine/deep learning.
ExpertTrack course overview
Course 1
Deep Learning on Azure with Python: AI for Beginners
Start your deep learning journey with this introductory Python-based course, exploring some of the fundamental applications of AI
3 weeks
6 hours per week
Week 1
Course Introduction
- About this Course
- Artificial Intelligence
- Machine Learning Fundamentals
- Azure Machine Learning Studio
- CloudSwyft Hands-On Lab 1
- Wrapping Up the Week
Week 2
Text Analytics and Image Processing
- Getting Started with Text Processing
- Introduction to Natural Language Processing
- Language Understanding Intelligent Service
- CloudSwyft Hands-On Lab 2
- Getting Started with Image Processing
- Wrapping Up the Week
Week 3
Image Processing, Bots and Beyond the Basics
- Working with Images and Video
- CloudSwyft Hands-On Lab 3
- Introduction to Bots
- Building Intelligent Bots
- CloudSwyft Hands-On Lab 4
- Beyond the Basics
- Where Do I Go From Here?
Course 2
Deep Learning on Azure with Python: The Basics of Python Programming
Learn the basics of Python programming, which underpins machine and deep learning models in Microsoft Cognitive Services.
3 weeks
5 hours per week
Week 1
Course Introduction
- About this Course
- Introduction to Python
- Introducing Variables and Types
- Python Lists
- Subsetting Lists
- Manipulating Lists
- Wrapping up the week
Week 2
Introduction to Functions, Methods and Objects
- Introduction to Functions
- Methods and Objects
- Python Packages
- NumPy and NumPy Arrays
- 2D NumPy Arrays
- Basic Statistics with NumPy
- Wrapping up the Week
Week 3
Boolean Logic, Pandas and Data Visualisation
- Boolean Logic and Control Flow
- Pandas
- Plotting with Matplotlib
- Histograms
- Data Visualisation
- Final Labs and Course Wrap Up
Course 3
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.
5 weeks
5 hours per week
Week 1
Introduction to Course and Machine Learning
- Course Introduction
- Introduction to Machine Learning
- Exploratory Data Analysis for Regression
- Visualisation for High Dimensions
- Wrapping Up the Week
Week 2
Data Exploration & Preparation
- Exploratory Data Analysis for Classification
- Data Cleaning
- Data Preparation
- Data Preparation and Cleaning using Python
- Feature Engineering
- Weekly Wrap-Up
Week 3
Regression & Classification
- Regression
- Putting Regression Concepts Into Practice
- Classification
- RoC Curves
- Putting Classification Concepts Into Practice
- Weekly Wrap-Up
Week 4
Principles & Techniques of Model Improvement
- Principles of Model Improvement
- Techniques for Improving Models
- Cross Validation
- Dimensionality Reduction
- Introduction to Decision Trees
- Ensemble Methods: Boosting
- Weekly Wrap-Up
Week 5
Machine Learning Algorithms & Unsupervised Learning
- Ensemble Methods: Descent & Decision Forests
- Advanced Machine Learning Algorithm: Neural Networks
- Advanced Machine Learning Algorithm: SVMs
- Advanced Machine Learning Algorithm: Naive Bayes Models
- Unsupervised Machine Learning
- Unsupervised Machine Learning Labs
- Wrapping up the Course
Course 4
Deep Learning on Azure with Python: Introduction to Deep Learning
Discover deep learning with Python using Microsoft Cognitive Toolkit, and explore deep learning algorithms and neural networks.
5 tests
4 weeks
5 hours per week
Week 1
Course Introduction
- About this Course
- What is Deep Learning?
- Introduction to Multi-class Classification Using Logistic Regression
- Wrapping Up the Week
Week 2
Multi-Class Classification and Multi-Layer Perceptron
- CloudSwyft Hands-On Lab 1
- Multi-Layer Perceptron
- CloudSwyft Hands-On Lab 2
- Wrapping Up the Week
Week 3
Introduction to CNN, RNN and LSTM
- Introduction to Convolution Neural Network - CNN
- Building a Convolutional Network
- CloudSwyft Hands-on Lab 3
- Recurrent Neural Network (RNN)
- Long Short Term Memory Block (LSTM)
- Wrapping Up the Week
Week 4
Text Classification with RNN and LSTM
- CloudSwyft Hands-On Lab 4
- Text Classification with RNN and LSTM
- CloudSwyft Hands-on Lab 5
- Wrapping up the course
Course 5
Deep Learning on Azure with Python: Reinforcement Learning
Discover reinforcement learning in this course covering how to frame reinforcement learning problems, algorithms, and more.
7 tests
6 weeks
5 hours per week
Week 1
Course Introduction
- About this Course
- What is Reinforcement Learning?
- Applications of Reinforcement Learning
- Comparisons To Machine Learning
- Elements of Reinforcement Learning
- CloudSwyft Hands-On Lab: RL Environments and Random Agent
- Wrapping Up the Week
Week 2
Introduction to Reinforcement Learning
- Bandits Framework
- Regret Minimisation
- Bridge to Reinforcement Learning
- CloudSwyft Hands-On Lab: Bandits
- Wrapping Up the Week
Week 3
The Reinforcement Learning Problem
- Agent and Environment Interface
- Markov Decision Process
- CloudSwyft Hands-On Lab 3
- Basics of Dynamic Programming
- Wrapping up the week
Week 4
Applying Dynamic Programming & Policy Evaluation
- CloudSwyft Hands-On Lab 4
- Temporal Difference Learning - Policy Evaluation
- Temporal Difference Learning - Policy Optimisation
- CloudSwyft Hands-On Lab 5
- Wrapping Up the Week
Week 5
Function Approximation and Deep Q-Learning
- Function Approximation
- CloudSwyft Hands-On Lab 6
- RL with Deep Neural Networks
- Extensions to Deep Q-Learning
- CloudSwyft Hands-On Lab 7
- Introduction to Policy Optimisation
- Wrapping Up the Week
Week 6
Policy Gradient and Actor Critic
- Likelihood Ratio Methods
- CloudSwyft Hands-On Lab 8
- Variance Reduction
- CloudSwyft Hands-On Lab 9
- Actor-Critic
- CloudSwyft Hands-On Lab 10
- Course Completion
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.
Download a PDF
How ExpertTracks work
Join an ExpertTrack to master new skills in your chosen specialist area. Work through a series of topic-focused courses at your own pace, and pass the final assessment to earn a digital certificate award which proves your expertise.
Decide if the ExpertTrack is right for you with free access to the full suite of courses and assessments for a week.
Pay a monthly subscription fee of $39 for as long as it takes you to complete the ExpertTrack. You can learn at your own pace and cancel at any time.
Receive a certificate for every completed course and pass the final assessment to earn a digital certificate.
Use your specialist training to progress further in your career or build expertise in areas you’re passionate about.
World-class learning with CloudSwyft Global Systems, Inc.
CloudSwyft has partnered with the top global technology companies to deliver cutting edge digital skills learning across the modern workplace.
This ExpertTrack is accredited by Microsoft
Learning on FutureLearn
Your learning, your rules
- Courses are split into weeks, activities, and steps to help you keep track of your learning
- Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
- Stay motivated by using the Progress page to keep track of your step completion and assessment scores
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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Start learning today - free 7-day trial
After your free trial you can:
- Pay $39 per month to keep learning online
- Have complete control over your subscription; you can cancel any time
- Work at your own pace and set your own deadlines at every stage
- Only pay while you’re learning; the subscription will cancel automatically when you finish
- Complete online assessments to test your knowledge and prove your skills
- Earn digital course certificates and a final award that you can share online, with potential employers, and your professional network
- Keep access to the content of courses you complete even after your subscription ends
FAQ
ExpertTracks are a series of online courses designed to help you master new skills in specialist areas. You pay a monthly subscription fee which includes access to all courses within the ExpertTrack, as well as assessments and the final digital certificate.
Each ExpertTrack comes with a 7-day free trial period. You may cancel your subscription at any time and your subscription will automatically cancel when you finish the courses and assessments in your chosen ExpertTrack.
Yes. All of our ExpertTracks come with a 7-day free trial. You may claim one free trial period per ExpertTrack.
You have seven days before you will be charged your first monthly subscription fee. When you join an ExpertTrack you automatically receive a 7-day free trial period. You can cancel at any time during the trial period and no payment will be taken from your account.
Please see our full refund policy here.
No, all of our ExpertTracks consist of fully online courses. This means you can take an ExpertTrack from anywhere in the world.
No. ExpertTracks are designed for you to master new skills in a specialist area. You will earn a digital certificate that proves your learning, but it does not carry accreditation.
If you’re looking for certified or accredited courses, many of our microcredentials offer university credit or professional certification.
Have more questions about ExpertTracks? Read the ExpertTracks FAQs, or contact us.