Machine Learning Course in Singapore

Machine Learning Training and Certification Program - An Overview

Machine learning training in the Singapore course syllabus is crafted by data scientist professionals. Therefore, it holds every mandatory Machine learning concept, including classification, time series modeling, supervised and unsupervised learning, regression, natural language processing, and more to meet the global industry requirements and helps aspirants crack any complicated machine learning exam interviews. Machine learning courses in Singapore offer the skills and knowledge required to become an expert in machine learning and unlock the power of the efficient field. Learn how to use Python in this machine learning, and also, the aspirants can quickly draw predictions from the information provided. A recent survey on machine learning has stated the demand for machine learning engineers is expected to reach 60% higher in the upcoming years, and the market is expected to reach $8.81 billion very soon.

A report on Gartner Inc states that machine learning technology will have around 2.3 million jobs by the end of this year. Most reputed organizations like Google, Adobe, Apple, Wipro, JO Morgan Chase & Co, Amazon, Facebook, Bosch group, Accenture, Uber, and more are hiring professionals with Machine learning skills to boost their business productivity. Developers, analytic managers, information architects, graduates, business analysts, analytics professionals, and experienced professionals can take this machine learning course in Singapore. According to glassdoor.sg, the average salary received by machine learning engineers in Singapore is about $110,556 per annum.

Syllabus of Machine Learning Training in Singapore

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 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 Machine Learning Training in Singapore

Besant Technologies provides flexible timings to all our students. Here is the Machine Learning Training in Singapore Branch Schedule. 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

Can’t find a batch you were looking for?

Request a Batch

Trainer Profile of Machine Learning Training in Singapore

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

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.

Key Features of Machine Learning Training in Singapore

Training Courses Reviews

Frequently Asked Questions