Advanced and Applied AI on Microsoft Azure by CloudSwyft Global Systems, Inc via Futurelearn: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based	Learning efforts 5-6 Hours Per Week

Course overview

Advanced and Applied AI on Microsoft Azure online course teaches the use of machine learning and AI to solve real-world problems. Advanced and Applied AI on Microsoft Azure certification by FutureLearn, aims to enhance the understanding of machine learning and AI using Microsoft Azure and Python.

The course covers four topics: Introduction to Machine Learning with Python and Azure Notebooks, Building Machine Learning Models on Azure, Applying Machine Learning and AI Techniques to Solve Business Problems, and Developing an AI Solution with Azure Cognitive Services. Each topic consists of a course that lasts for about four weeks, with 5-6 hours of study per week. Upon completion of the Advanced and Applied AI on Microsoft Azure certification course, a digital certificate is awarded. The course level is intermediate, which requires some prior knowledge of Python and basic statistics.

The course aims to enhance the understanding of machine learning and AI using Microsoft Azure and Python. It also prepares for related exams including Microsoft Azure AI Engineer Associate (AI-100) and Microsoft Azure AI Fundamentals (AI-900)

Course and certificate fees

The Advanced and Applied AI on Microsoft Azure certification fee comes at a monthly subscription price of Rs. 900.

Advanced and Applied AI on Microsoft Azure fee structure

Course Name	Fee
Advanced and Applied AI on Microsoft Azure	Rs. 900 p.m.

certificate availability

Yes

certificate providing authority

Futurelearn

Who it is for

Software developer Data scientist Database architect Cloud solution architect Big data engineer Devops engineer

The Advanced and Applied AI on Microsoft Azure certification syllabus is for anyone who wants to learn how to apply machine learning and AI to solve real-world problems using Microsoft Azure and Python. It is especially suitable for those who are interested in pursuing a career in data science, machine learning, or AI, as it will help them prepare for related exams and certifications. Some of the job titles that might benefit from this course include. For example

Eligibility criteria

Certification Qualifying Details

Completion of Advanced and Applied AI on Microsoft Azure training is enough for certification.

What you will learn

During Advanced and Applied AI on Microsoft Azure classes, participants will be able to:

How to use Python and Azure Notebooks to perform basic machine learning tasks, such as data preparation, feature engineering, model selection, and evaluation.
How to use Azure Machine Learning and Azure Databricks to build, train, and deploy machine learning models on the cloud.
How to apply machine learning and AI techniques to various business scenarios, such as customer segmentation, product recommendation, sentiment analysis, and fraud detection.
How to use Azure Cognitive Services and Azure Bot Service to develop an AI solution that leverages natural language processing and computer vision capabilities.

The syllabus

Microsoft Future Ready: Using Python Programming to Explore the Principles of Machine Learning

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

Data Exploration & Preparation

Exploratory Data Analysis for Classification
Data Cleaning
Data Preparation
Data Preparation and Cleaning using Python
Feature Engineering
Weekly Wrap-Up

Regression & Classification

Regression
Putting Regression Concepts Into Practice
Classification
RoC Curves
Putting Classification Concepts Into Practice
Weekly Wrap-Up

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

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

Applied Artificial Intelligence: Speech Recognition Systems

Course Introduction

About this Course
Introduction to Fundamental Theory
CloudSwyft Hands-On Lab 1
Speech Signal Processing
CloudSwyft Hands-On Lab 2
Wrapping Up the Week

Acoustic and Language Modeling

Acoustic Modelling
Deep Neural Network Acoustic Models
CloudSwyft Hands-On Lab 3
Language Modelling
Language Model Evaluation and Operations
Wrapping up the week

Speech Decoding and Advanced Acoustic Modeling Techniques

Week 3 Welcome and CloudSwyft Hands-On Lab 4
Speech Decoding
WFST, Acceptors and Graph Composition
CloudSwyft Hands-On Lab 5
Advanced Acoustic Modeling Techniques | Improved Objective Functions
Course Completion

Applied Artificial Intelligence: Natural Language Processing

Course Introduction

About this Course
Introduction to NLP
NLP and Text Processing
Neural Models for Machine Translation and Conversation Generation
CloudSwyft Hands-On Lab 1
Wrapping up the week

Deep Semantic Similarity Model (DSSM)

Deep Semantic Similarity Model and its Applications
Deep Semantic Similarity Model for Information Retrieval
Deep Semantic Similarity Model for Entity Ranking
CloudSwyft Hands-On Lab 2
Deep Reinforcement Learning
Vision-Language Multimodal Intelligence
Wrapping up the Week

Natural Language Understanding

Natural Language Understanding
Continuous Word Representation
Neural Knowledge Base Embedding
Knowledge-Based Question Answering
CloudSwyft Hands-On Lab 3
Wrapping up the Week & Course Completion

Applied Artificial Intelligence: Computer Vision and Image Analysis

Introduction and The 5 Algorithms

About this Course
Image Processing, Application and Segmentation
Image Features and Classical Methods
Clustering and Region Growing
Wrap Up

Object Classification and Detection

Template Matches, Edges and Corners
Histogram of Orientated Gradients
Object Classification And Detection
Wrap Up

CNNs, Deep Learning & Deep Segmentation

Convolutional Neural Networks (CNN)
Deep Learning
Deep Segmentation
Wrap Up

FCN, Transfer Learning and Course Wrap Up

Fully Convolutional Approaches (FCNs)
Deep Segmenters & Transfer Learning
Final Assessment and Course Wrap Up

Admission details

Follow the steps below to join the online course.

Step 1- Click on the link below: https://www.futurelearn.com/experttracks/ai-engineer-with-microsoft-azure

Step 2- Register to the Futurelearn platform

Step 3- Subscribe to the FutureLearn service and start learning

How it helps

Advanced and Applied AI on Microsoft Azure certification benefits include:

Learn advanced machine learning and AI with Azure and Python.
Prepare for globally recognized exams: AI-100 and AI-900.
Solve real-world problems with machine learning and AI.
Learn from and interact with experts and peers.

FAQs

What is the GPHR certification?

The GPHR certification is a global, competency-based credential that is designed to validate the skills and knowledge of an HR professional who operates in a global marketplace.

What will I learn in the Advanced and Applied AI on Microsoft Azure online course?

Upon completion of the course you will learn how to participate in the development and implementation of the HR strategy to align with the global business strategy and implement workforce planning.