Discover deep learning in this ExpertTrack, covering AI fundamentals, machine learning, and deep learning with Python, using Microsoft Azure Cognitive Services
5-6 hrs per week
Approx 21 weeks
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Level
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Median base salary
£45,000
UK job openings/month
1,724
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
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