Azure Machine Learning Training

About Azure Machine Learning Certification Training Course

Azure Machine Learning certification training course makes you understand regression analysis, clustering, deploying web services and solving data processing challenges. Azure Machine Learning training course helps you in understanding machine learning with azure. Azure Machine Learning Certification Training Course is a placement oriented training that provides you work in big corporate houses.

After the completion of the Azure Machine Learning training course, you will get certification like Microsoft Azure Machine Learning Certificate. The average salary in Azure Machine Learning is $136,043.

Azure Machine Learning Course Syllabus

Azure Training Syllabus

Module 1: Why Cloud? (Duration- 1hrs)

• Why Cloud and What is Cloud Computing?
• Identify the features and benefits of cloud computing
• Different types of Cloud Computing deployment model
• Public Cloud, Private Cloud, Hybrid Cloud
• Virtualization – An essential in cloud
• Virtualization in Cloud model
• Different types of virtualization
• Hypervisor – Benefits
• Different types of services and their difference in Cloud computing
• IaaS, PaaS, SaaS
• Importance of scaling in cloud computing
• Different types of scaling and its applications
• Issues we overcome using cloud and applications
• Cost model that we use in cloud computing

Click Here to Check Latest Updated – Microsoft Azure Interview Questions and Answers

Module 2: A kick start on the Microsoft Azure platform (Duration-1hrs)

• Microsoft Azure – An High-level overview
• Creation of Azure account
• Overview of the services provided in Azure
• Learn support center help and other controls

Module 3: Managing Microsoft Azure Subscription (Duration-1hrs)

• Creating subscription for the account
• Cost center and tagging
• Azure policies

Module 4: Azure Resource Management (Duration-2hrs)

• Managing and analyzing Azure resource
• Diagnostics and baseline environment
• Creating alerts and metrics
• Managing costs
• Log analysis

Module 5: Azure Virtual Machines (Duration-5hrs)

• Introduction to Virtual machine architecture
• Azure Virtual machine – an overview
• Understanding different families of virtual machines
• Understanding the plans and costs of virtual machines
• Creating a virtual machine
• Connecting the virtual machine remotely
• Understanding VM Availability
• Understanding and setting virtual machine monitoring
• Virtual Machine scale sets (VMSS)
• Creating windows and Linux virtual machines

Module 6: Managing Azure Virtual Machines (Duration-2hrs)

• Adding additional data disks to Virtual machine
• Adding network interface cards to virtual machines
• Changing different VM size
• Redeploying virtual machines

Module 7: Azure Virtual machine backups (Duration-2hrs)

• Understanding virtual machine backups
• Virtual machine backup jobs and restores
• Hands-on on virtual machine concepts

Module 8: Azure Virtual Networks (Duration-6 hrs)

• Understanding Basic networking
• Understanding CIDR
• Creation of virtual networks
• Public IP addressing concepts
• Learning network routing on azure
• Setup virtual networks peering between different virtual networks
• Vent to vent connection

Module 9: Introduction to Load Balancing (Duration-2 hrs)

• Setup Load Balancer
• Front End IP Configuration

Module 10: Azure network security groups (Duration-1hr)

• An intro to Network security groups
• Implementing Network security group rules

Module 11: Azure DNS Services (Duration-2hrs)

• Azure DNS services introduction
• Assigning custom domains

Module 12: Azure AD – Basic vs Premium (Duration-5hrs)

• Introduction and Creating Azure AD
• Adding our Custom Domains
• Learn about AD Identity Protection
• How to implement Self Service Password Reset
• Conditional Access and Access Reviews

Module 13: Implementing MFA (Duration-1hrs)

• Azure AD MFA – An introduction
• Azure AD Conditional Access
• Configuring Fraud Alerts
• MFA One Time Bypass

Module 14: Azure RBAC  (Duration-1hrs)

• Understanding Azure Role-based access control (RBAC)
• Creating custom RBAC

Module 15: Creating and configuring storage accounts (Duration-3hrs)

• Create Storage Account
• Virtual Networks and Firewalls
• Access Keys and SAS
• Storage Explorer
• Log Analytics
• Redundant Storage

Machine Learning Training Syllabus

Module 1- Introduction to Data Analytics (Duration : 04:00:00 hrs)

Objectives:

• This module introduces you to some of the important keywords in R like Business Intelligence, Business Analytics, Data, and Information.
• You can also learn how R can play an important role in solving complex analytical problems.
• This module tells you what is R and how it is used by giants like Google, Facebook, etc.
• Also, you will learn the use of ‘R’ in the industry, this module also helps you compare R with other software in analytics, install R and its packages.

Topics

• Business Analytics, Data, Information
• Understanding Business Analytics and R
• Compare R with other software in analytics
• Install R
• Perform basic operations in R using the command line
• Learn the use of IDE R Studio
• Use the ‘R help’ feature in R

Module 2- Introduction to R programming (Duration: 03:00:00 hrs)

Objectives:

• This module starts with the basics of R programming like data types and functions.
• In this module, we present a scenario and let you think about the options to resolve it, such as which datatype should one to store the variable or which R function that can help you in this scenario.
• You will also learn how to apply the ‘join’ function in SQL.

Topics

• Variables in R
• Scalars
• Vectors
• Matrices
• List
• Data frames
• Using c, Cbind, Rbind, attach and detach functions in R
• Factors

Module 3- Data Manipulation in R (Duration : 04:00:00 hrs)

Objectives:

• In this module, we start with a sample of a dirty data set and perform Data Cleaning on it, resulting in a data set, which is ready for any analysis.
• Thus using and exploring the popular functions required to clean data in R.

Topics

• Data sorting
• Find and remove duplicates record
• Cleaning data
• Recoding data
• Merging data
• Slicing of Data
• Merging Data
• Apply functions

Module 4- Data Import techniques in R (Duration: 04:00:00 hrs)

Objectives:

• This module tells you about the versatility and robustness of R which can take-up data in a variety of formats, be it from a CSV file to the data scraped from a website.
• This module teaches you various data importing techniques in R.

Topics

• Reading Data
• Writing Data
• Basic SQL queries in R
• Web Scraping

Module 5- Exploratory data Analysis (Duration: 05:00:00 hrs)

Objectives:

• In this module, you will learn that exploratory data analysis is an important step in the analysis.
• EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis. You will also learn about the various tasks involved in a typical EDA process.

Topics

• Box plot
• Histogram
• Pareto charts
• Pie graph
• Line chart
• Scatterplot
• Developing Graphs

Module 6- Basics of Statistics & Linear & Logistic Regression (Duration : 05:00:00 hrs)

Objectives:

• This module touches the base of Descriptive and Inferential Statistics and Probabilities & ‘Regression Techniques’.
• Linear and logistic regression is explained from the basics with the examples and it is implemented in R using two case studies dedicated to each type of Regression discussed.

Topics

• Basics of Statistics
• Inferential statistics
• Probability
• Hypothesis
• Standard deviation
• Outliers
• Correlation
• Linear & Logistic Regression

Module 7- Data Mining: Clustering techniques, Regression & Classification (Duration : 04:00:00 hrs)

Objectives:

• Linear and logistic regression is explained from the basics with the examples and it is implemented in R using two case studies dedicated to each type of Regression discussed.
• The two Machine Learning types are Supervised Learning and Unsupervised Learning and the difference between the two types.
• We will also discuss the process involved in ‘K-means Clustering’, the various statistical measures you need to know to implement it in this module.

Topics

• Introduction to Data Mining
• Understanding Machine Learning
• Supervised and Unsupervised Machine Learning Algorithms
• K- means clustering

Module 8- Anova & Sentiment Analysis (Duration : 02:00:00 hrs)

Objectives:

• This module tells you about the Analysis of Variance (ANOVA) Technique.
• The algorithm and various aspects of Anova have been discussed in this module
• Additionally, this module also deals with Sentiment Analysis and how we can fetch, extract and my live data from Twitter to find out the sentiment of the tweets.

Topics

• Anova
• Sentiment Analysis

Module 9- Data Mining: Decision Trees and Random Forest (Duration : 03:00:00 hrs)

Objectives:

• This module covers the concepts of Decision Trees and Random Forest.
• The algorithm of Random Forests is discussed in a step-wise approach and explained with real-life examples.

Topics

• Decision Tree
• Concepts of Random Forest
• Working of Random Forest
• Features of Random Forest

Module 10- Project work (Duration : 10:00:00 hrs)

• 2 Real-time projects

Upcoming Batch Schedule for Azure Machine Learning Training

Besant Technologies provides flexible timings to all our students. Here is the Azure Machine Learning Training Class Schedule in our branches. If this schedule doesn’t match please let us know. We will try to arrange appropriate timings based on your flexible timings.

• 25-11-2024 Mon (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 21-11-2024 Thu (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 23-11-2024 Sat (Sat - Sun)Weekend Batch 11:00 AM (IST) (Class 3Hrs) / Per Session Get Fees

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Trainer Profile of Azure Machine Learning Training Syllabus

Our Trainers provide complete freedom to the students, to explore the subject and learn based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates are free to ask any questions at any time.

• More than 7+ Years of Experience.
• Trained more than 2000+ students in a year.
• Strong Theoretical & Practical Knowledge.
• Certified Professionals with High Grade.
• Well connected with Hiring HRs in multinational companies.
• Expert level Subject Knowledge and fully up-to-date on real-world industry applications.
• Trainers have Experienced on multiple real-time projects in their Industries.
• Our Trainers are working in multinational companies such as CTS, TCS, HCL Technologies, ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies etc

Azure Machine Learning Exams & Certification

Besant Technologies Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.

Our certification at Besant Technologies is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s of the world. The certification is only provided after successful completion of our training and practical based projects.

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