Skill behind modern AI
Recommendation engines, fraud checks and chatbots all start with the machine learning methods taught here.
Livewire · Special Programs
Machine Learning Course in Vellore, Katpadi & Ranipet
Learn the statistics and algorithms behind machine learning, and build classification, regression, clustering and neural-network models in Python and R.
2 levels56–96 h148 topics3 centresClassroom · Online · Hybrid
01What is Machine Learning
What is Machine Learning? In plain words.
Machine learning is a branch of artificial intelligence where a computer learns patterns from data instead of following fixed rules. You feed it past examples – sales, sensor readings, medical records, customer reviews – and it learns to predict, classify or group new data. The work rests on statistics and is written in languages such as Python and R, using open-source libraries. This page covers two programmes: one in Python and a longer one using both R and Python.
Companies use machine learning to forecast demand, flag fraud, recommend products, predict machine failure, read text and sort customer feedback. IT services firms, banks, e-commerce, healthcare and manufacturing all hire people who understand these models. Employers look for candidates who know the statistics behind a model, can prepare messy data, choose the right algorithm and judge results with measures like precision and recall – exactly what this course trains.
With VIT and many engineering and arts colleges around Katpadi and Vellore, students here can add machine learning to their degree and aim for AI and analytics roles in Chennai and Bengaluru, both within easy reach.
What you will be able to do
- Write Python programs using data structures, functions, modules, file handling and exception handling
- Describe data with central tendency, dispersion, probability distributions and correlation
- Prepare and pre-process raw data for modelling
- Build classification models with Decision Tree, KNN, SVM, Naïve Bayes and Logistic Regression
- Build and compare Linear, Multiple, Poisson, Lasso and Ridge regression models
- Group data with hierarchical, k-means, k-Medoids and DBSCAN clustering and reduce dimensions with PCA
- Evaluate models using a confusion matrix, precision, recall and F-score
- Build simple ANN and RNN models and apply basic text mining and NLP
02Why learn it
Why learn Machine Learning now?
Six reasons students and professionals in Vellore district pick this skill.
Strong statistics base
You learn distributions, correlation and confidence intervals first, so models make sense instead of feeling like magic.
Wide range of algorithms
Decision trees, KNN, SVM, Naïve Bayes, many regression types, clustering and PCA are all covered with case studies.
Python and R options
Pick the Python programme or the longer course that teaches both R and Python.
First steps into deep learning
You finish with neural networks (ANN) and recurrent networks (RNN), plus text mining and NLP basics.
Project-based learning
Every block ends with a case study, and the course closes with a project you can show in interviews.
03Who can learn
Who can join this course?
BE/BTech students
CSE, IT, ECE and other branches who want an AI and data skill for placements.
BSc and MSc students
Computer Science, Mathematics and Statistics students who want to apply theory to real data.
BCA and MCA students
Students who already code and want to move towards data science roles.
Software professionals
Developers and testers planning a shift into ML or data engineering work.
Data and MIS analysts
Analysts who want to go beyond reports and build predictive models.
Researchers and PhD scholars
Scholars who need statistical modelling and ML for their research data.
Before you start: Basic computer skills and school-level maths are needed. Some exposure to programming helps, but the course starts with Python (and R in the 96-hour course) from the basics.
04Levels & syllabus
Every Machine Learning level, topic by topic.
2 programmes on one page. Pick a level to see its modules and every topic covered.
Foundation level
Course on Machine Learning using Python
Students and professionals who want a focused 56-hour machine learning course in Python.
56 hours9 modules · 70 topicsCode LWC158DSCertificate: Livewire network
9 modules · 70 topics
01Introduction and Python Essentials10 topics
Introduction to Machine LearningHistory and applications of Machine LearningIntroductory concepts of PythonData structuresControl flowFunctionsModules and packagesFile input and outputException handlingStandard libraries
02Statistics for Machine Learning10 topics
Preliminaries of statisticsStatistical data typesMeasures of central tendency and dispersionProbability theoryNormal distributionScatter diagramCorrelation analysisConfidence intervalT-distributionCase studies
03Model Evaluation and Pre-processing5 topics
Confusion matrixPrecisionRecallF-scoreData pre-processing
04Classification Algorithms8 topics
Decision TreeGINI indexEntropyK-Nearest Neighbours (KNN)Support Vector Machine (SVM)Naïve Bayes classifierLogistic regressionCase studies
05Regression Analysis11 topics
Regression analysisLinear regressionMultiple linear regressionRandom ForestPoisson regressionLasso and Ridge regressionZero-inflated regressionNegative binomial regressionMultinomial regressionSurvival analysisCase study
06Clustering and Dimension Reduction12 topics
Web extractionEuclidean distanceManhattan distanceHierarchical clusteringk-means clusteringk-MedoidsDBSCANPAMCLARADimension reductionPrincipal Component Analysis (PCA)Case study
07Text Mining and NLP4 topics
Word cloudIntroduction to text miningData extraction and NLPCase study
08Deep Learning Basics9 topics
Introduction to deep learningIntroduction to neural networksANN for classificationANN for regressionIntroduction to RNNDifference between ANN and RNNMethods and functions of RNNRNN algorithm writingRNN case study
09Projects1 topics
End-to-end machine learning project
Foundation level
Course on Machine Learning
Learners who want a deeper 96-hour course that teaches machine learning in R and then applies key models in Python.
96 hours10 modules · 78 topicsCode LWC148Certificate: Livewire network
10 modules · 78 topics
01R Programming Foundations6 topics
Introduction to Machine LearningAbout R programmingInstalling RStudioWorking in RStudioDatasets and packagesFundamentals of R programming
02Descriptive Statistics5 topics
Preliminaries of statisticsData typesMeasures of central tendency and dispersionGraphical representationProbability theory
03Distributions and Inference11 topics
Normal distributionSkewness and kurtosisStandard normal distribution (Z-score)Q-Q plotBinomial and Poisson distributionScatter diagramCorrelation analysisConfidence intervalZ-distributionT-distributionCase study
04Model Evaluation5 topics
Pre-program preparationConfusion matrixPrecisionRecallF-score
05Classification Algorithms9 topics
Classification algorithmsDecision TreeGINI indexEntropyKNNSVMNaïve Bayes classifierLogistic regressionCase studies
06Regression Analysis11 topics
Regression analysisLinear regressionMultiple linear regressionRandom ForestPoisson regressionLasso and Ridge regressionZero-inflated regressionMultinomial regressionSurvival analysisWeb extractionCase study
07Clustering and Dimension Reduction12 topics
Introduction to clusteringEuclidean distanceManhattan distanceHierarchical clusteringk-means clusteringk-MedoidsDBSCANCLARADimension reductionPCAWord cloudCase studies
08Machine Learning with Python7 topics
Getting started with Python and packagesBasic statistics in PythonGraphical representation in PythonLinear regression in PythonLogistic regression in PythonHierarchical clustering in Pythonk-means clustering in Python
09Text Mining and Deep Learning11 topics
Introduction to text miningData extraction and NLPIntroduction to deep learningIntroduction to neural networksANN for classificationANN for regressionIntroduction to RNNDifference between ANN and RNNMethods and functions of RNNRNN algorithm writingRNN case study
10Projects1 topics
End-to-end machine learning project
05Choose your level
Which level is right for me?
Choose Machine Learning using Python (56 hours) if you want to work mainly in Python and finish faster. Choose the Course on Machine Learning (96 hours) if you want more time on statistics, learn R for analysis and also apply the main models in Python. After either, Artificial Intelligence or Data Science are natural next steps.
| Programme | Level | Hours | Best for |
|---|---|---|---|
| Course on Machine Learning using Python Code LWC158DS | Foundation | 56 h | Students and professionals who want a focused 56-hour machine learning course in Python. |
| Course on Machine Learning Code LWC148 | Foundation | 96 h | Learners who want a deeper 96-hour course that teaches machine learning in R and then applies key models in Python. |
Foundation
Course on · Essential · Certificate · SKEP · Executive DiplomaStart here. Core tools, workflow and a practice project.
Professional
Proficient · ProfessionalIndustry-style exercises, advanced features and a portfolio project.
Master
Advanced · Expert · MastersComplete programmes that combine several tools and a capstone project.
06Hands-on
Projects you will build
You learn by making real deliverables – reviewed by your trainer before certification.
Customer churn classifier
Pre-process a customer dataset and compare Decision Tree, KNN and Logistic Regression using precision, recall and F-score.
House price or sales forecast
Build linear and multiple regression models, then try Lasso and Ridge to see how regularisation changes results.
Customer segmentation
Group customers with k-means and hierarchical clustering and use PCA to visualise the clusters.
Review text analysis
Extract text, clean it and build a word cloud to find the most common themes in product reviews.
Neural network model
Train a simple ANN for classification and compare it with a traditional algorithm on the same data.
Tools & features covered
PythonR and RStudioPython standard libraries and packagesR packagesClassification and regression algorithmsClustering algorithms and PCAConfusion matrix and evaluation metricsText mining and word cloudsArtificial Neural Networks (ANN)Recurrent Neural Networks (RNN)
Talk to a counsellor about Machine Learning
Get the full syllabus PDF, current fee, offers and the next batch date on WhatsApp – usually within minutes during centre hours.
07Careers
Jobs you can apply for after Machine Learning
Roles that list this skill in Indian job postings.
Junior Machine Learning Engineer
Prepares data, trains models and tests their accuracy under senior guidance.
Data Scientist (Associate)
Explores data, builds predictive models and explains findings to business teams.
Data Analyst
Cleans and analyses data and uses statistics to answer business questions.
ML Intern / Trainee
Supports model building, data labelling and experiments in an AI team.
NLP Engineer (Entry Level)
Works on text data for tasks like classification, search and sentiment.
Business Analyst – Analytics
Uses models and statistics to support forecasting and planning decisions.
Research Assistant – Data
Applies statistical and ML methods to research datasets in labs and institutes.
Salary you can expect
Fresher0–2 years₹3–5.5 LPA
Experienced3–5 years₹6–12 LPA
Senior6+ years₹14–25 LPA
Indicative ranges for India; pay varies by company, city, skills and experience. Figures in lakh per annum (LPA).
Industries that use it
IT Services and ConsultingBanking and Financial ServicesE-commerce and RetailHealthcare and Life SciencesManufacturingTelecomInsuranceEducation and Research
Companies that use these skills
TCSInfosysWiproHCLTechCognizantAccentureTech MahindraZohoFreshworksFlipkartAmazonSwiggyHDFC BankICICI BankMu SigmaFractal Analytics
Examples of well-known companies and sectors in India that use these skills. They are not CareerKraft partners or recruiters.
Your career path
1
ML Intern / Data Analyst Trainee
Clean data, run basic statistics and help build simple models.
2
Junior ML Engineer / Data Analyst
Build and evaluate models for defined business problems.
3
Machine Learning Engineer / Data Scientist
Own model choice, feature work and deployment support for projects.
4
Senior Data Scientist
Design solutions, mentor juniors and work with stakeholders on business impact.
5
ML Lead / AI Architect
Lead teams and set the technical direction for AI and data products.
Placements
Students placed from our centres
Vignesh K
Service Lab Assistant
Metric Measurement Technologies
Proficient in AutoCAD Electrical
AJ
Aminudeen J
Intern
Aptagrim Consulting Pvt. Ltd, Hyderabad
Master Program in Software Development
AC
Ashwini C
Teacher
Springdays CBSE School, Vellore
Course on Python
SB
Shilpa B
Associate Networker, Intern
Selfmade Ecom Pvt. Ltd, Rinex
Internship available: Machine Learning internship (20 hours) – a short project-based track for college students.
08How you learn
Classroom, online or both.
Same syllabus and certificate in every mode. Your counsellor confirms the mode based on trainer availability for your batch.
Classroom
Learn in our labs at Katpadi, Vellore or Ranipet with your trainer beside you and classmates to build with.
Online
Live sessions from home with the same syllabus, projects and certificate. Good if you cannot travel every day.
Hybrid
Lab days plus online sessions around college or work. The mode depends on trainer availability for your batch.
Certificate
On completing a level and its project assessment, you receive the course certificate of the Livewire network, issued through CareerKraft as the authorised training partner.
Batches & timings
Weekday, weekend and fast-track batches within centre hours (Mon–Sat 9:30 AM – 6:30 PM · Sun 9:00 AM – 2:00 PM). Ask for the next start date at your centre.
Fees & EMI
The fee depends on the level and mode. Your counsellor shares the current fee, offers and EMI options on WhatsApp.
Why learn at CareerKraft
Authorised partner training
Structured syllabi and certificates from the CADD Centre, Livewire and SynergySBS networks.
Learn by doing
Hands-on lab work and a project assessed before you are certified.
Personal attention
Industry-experienced trainers and batches small enough to ask questions.
Placement support
Resume help, mock interviews and job leads when you are ready – no false promises.
Career guides that include this course
11Where to learn
Learn Machine Learning at any of 3 centres
Same syllabus, trainer standard and certificate at every centre. Tap the centre you want.
Machine Learning in Katpadi
Near Aascars Cinemas, Katpadi
Livewire Katpadi
Machine Learning in Vellore
Near Raja Theatre, Vellore
Livewire Vellore
Machine Learning in Ranipet
Near SBI, Muthukadai, Ranipet
Livewire Ranipet
09FAQ
Machine Learning course – your questions answered
12 answers about levels, duration, eligibility, certificate, placement support and fees.
Still have a question? The counsellor at the centre you prefer replies on WhatsApp.
Ask on WhatsAppWhat is machine learning?
Machine learning is a way of making computers learn patterns from past data so they can predict or classify new data. It is the base of many AI features such as recommendations, fraud detection and text analysis.
Who can join this machine learning course?
Engineering, science, BCA/MCA students and working professionals can join. You need basic computer skills and school-level maths; Python (and R in the longer course) is taught from the basics.
How long are the courses?
The Course on Machine Learning using Python is 56 hours. The Course on Machine Learning, which uses R and Python, is 96 hours.
Which course should I choose?
Pick the 56-hour Python course if you want a faster, Python-only route. Pick the 96-hour course if you want deeper statistics, R skills and more case studies.
Can I learn online or in hybrid mode?
Yes. Classes are offered in classroom, online or hybrid mode, depending on trainer availability.
Is a free demo class available?
Please ask the counsellor at your chosen centre on WhatsApp or phone about demo sessions and upcoming batches.
Will I get a certificate?
Yes, you receive a course completion certificate after finishing the programme and its project.
Is placement support provided?
Yes, we offer placement support such as resume building, mock interviews and job leads. We do not promise or guarantee a job.
What is the course fee?
The counsellor at your chosen centre will share the current fee, offers and EMI options on WhatsApp.
Do I need a laptop?
Lab systems are available for classroom batches. A laptop with at least 8 GB RAM is useful for practice at home and is needed for online classes.
What jobs and salary can I expect?
Freshers usually start as data analysts, ML trainees or junior ML engineers, often around ₹3–5.5 LPA. Pay rises with experience and is higher in Chennai and Bengaluru; figures are indicative and vary by company and skills.
Where are classes held and what are the timings?
Classes run at all three centres – Katpadi, Vellore and Ranipet. Timings are Monday to Saturday 9:30 am–6:30 pm and Sunday 9:00 am–2:00 pm.
10Keep exploring
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View course Listed in:
Local pages: Machine Learning course in Katpadi · Machine Learning course in Vellore · Machine Learning course in Ranipet · Machine Learning course in Tiruvannamalai · Machine Learning course in Tirupattur
Start today
Get the Machine Learning syllabus, fees & batch dates
Fill this in and WhatsApp opens with your details, addressed to the centre you choose. The counsellor replies with the full syllabus, current fee, offers and the next batch.
- Free counselling and demo class
- Real projects and placement support
- Classroom, online or hybrid batches
- Replies Mon–Sat 9:30 AM – 6:30 PM · Sun 9:00 AM – 2:00 PM