Machine Learning Training in India

Machine Learning Training Course in India

Machine Learning Training Course in India holds great value. You can learn it with R or Python programming language. At Besant Technologies, we provide training courses for both. With the Machine Learning Certification Training Course in India, you can train the machine to analyze, make predictions and take decisions. It is helpful for repetitive and complex tasks.

This versatile training course at Besant Technologies will provide you with lessons that will help you apply Machine Learning in real-time scenarios like identifying spam emails, creating a movie recommendation list, creating a Chabot, and more.

About Machine Learning Certification Training Course in India

The Machine Learning Certification Training Course in India at Besant Technologies will cover all the major topics required to gain a deeper knowledge of the subject. This Machine Learning Training Course includes hands-on projects and assignments based on real-time cases.

With the Machine Learning Online Training in India at Besant Technologies, you will get the flexibility to complete your course at your convenient pace. Our well-experienced trainers with strong practical and theoretical knowledge will give you complete knowledge about each topic.

Syllabus of Machine Learning Training in India

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 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 (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

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Upcoming Batch Schedule for Machine Learning Training in India

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

• 30-12-2024 Mon (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 26-12-2024 Thu (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 28-12-2024 Sat (Sat - Sun)Weekend Batch 11:00 AM (IST) (Class 3Hrs) / Per Session Get Fees

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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

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