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Machine Learning Certification Training in Melbourne

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Machine Learning Certification Training Course in Melbourne by GangBoard is an industry-oriented training. In Machine Learning Certification Training by GangBoard in Melbourne you will gain mastery over concepts such as supervised learning, unsupervised learning, statistics, probability, decision tree, linear regression, random forest, logistic regression. As part of Machine Learning Online Training by GangBoard in Melbourne you will work on Real-world projects and get Hands-on Experience. Course modules for Machine Learning Course by GangBoard in Melbourne have been prepared by GangBoard experts who have many years of working experience in industry. They syllabus of Machine Learning Training by GangBoard in Melbourne resonates with the current demands of industry and hence this Machine Learning Training by GangBoard in Melbourne will help you become successful Machine Learning Professional.GangBoard awards Certification to those who successfully complete the training. GangBoard certificates hold significance as they are recognized by all top companies and stand for competence and quality. As Machine Learning Engineer you will be able to earn $146,085 per annum.

Reviews

1342 Ratings

Total Learners

1567 Learners

Course Duration

30 Hours

Assignments Duration

20 Hours

About Course

Machine Learning Course by GangBoard in Melbourne represent all-inclusive program for those who want to gain mastery over several aspects of Machine Learning. In Machine Learning Certification Training by GangBoard in Melbourne you will learn about various modules of Machine learning, SVM or Super Vector Machines and work on some of the best practices utilized in industry related to Machine Learning.

What will you learn in Machine Learning Training in Melbourne?

You will learn about the following concepts in Machine Learning Training by GangBoard in Melbourne:

Use of data for machine training
Artificial Neural Networks
Logistic and Linear regression
Support Vector Machines
Machine Learning System design
Data modelling and Principal Component Analysis

Who should go for Machine Learning Certification Training in Melbourne?

If you want to make a career in Machine Learning domain, Machine Learning Training by GangBoard in Melbourne is ideal for you. Machine Learning Training by GangBoard in Melbourne should also be taken up by analytics professionals, Data Scientists, professionals of search engine domains and e-commerce etc.

What are the prerequisites for Machine Learning Training in Melbourne?

There are no prerequisites for Machine Learning Training by GangBoard in Melbourne. Anybody who wants to learn Machine Learning can take up Machine Learning Training by GangBoard in Melbourne without any prior skills.

What are Machine Learning job opportunities in Melbourne?

Due to Australia’s economy, Machine Learning jobs are the highest paid in the world. All IT-jobs that exist are mostly located in Melbourne. Due to this, Machine Learning job opportunities are growing in Melbourne. If you are skilled Machine Learning engineer you can easily increase the profit of the company. Melbourne is one of the best places to make your career grow as Machine Learning Certified professional.

What is Machine Learning market trend in Melbourne?

Australian scenario for Machine Learning jobs in Melbourne has been the best. Now with the booming IT sectors it is more certain than before. Companies are looking for Machine Learning certified professionals with the right skills and knowledge to apply in the industry oriented scenarios. With Machine Learning Training by GangBoard in Melbourne you will make your mark in this domain and take your career to new heights.

Why you should take up Machine Learning Training in Melbourne?

Machine Learning has been one of the prominent domains. Machine Learning concepts are being deployed in almost all organizations. Search engines and self-driving cars are some of the examples of applications of Machine Learning. Machine Learning has made our lives simpler. Machine Learning Training by GangBoard in Melbourne will help you excel in your career and seize the best jobs in the industry.

Machine Learning Training Syllabus

Download Syllabus

Module 1- Introduction to Data Analytics

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 the giants like Google, Facebook, etc.
Also, you will learn 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 command line
Learn the use of IDE R Studio
Use the ‘R help’ feature in R

Module 2- Introduction to R programming

Objectives:

This module starts from the basics of R programming like datatypes 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

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

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

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

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
Inferencial statistics
Probability
Hypothesis
Standard deviation
Outliers
Correlation
Linear & Logistic Regression

Module 7- Data Mining: Clustering techniques, Regression & Classification

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

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 mine 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

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

2 Real-time projects

Machine Learning Interview Questions and Answers

Upcoming Batches

Start Date	End Date	Time (EST) ( UTC -5)	Day
13 Dec 2019	10 Jan 2020	(08:30 PM - 11:00 PM)	Fri,Sat
14 Dec 2019	11 Jan 2020	(08:30 AM - 11:00 AM)	Sat,Sun
16 Dec 2019	13 Jan 2020	(08:30 PM - 10:00 PM)	Mon-Fri
17 Dec 2019	14 Jan 2020	(10:00 AM - 11:30 AM)	Tue-Sat
17 Dec 2019	14 Jan 2020	(08:30 AM - 10:00 AM)	Tue-Sat