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Data Science Course in Tambaram

(4.9) 19854 Ratings
  • Join the Best Data Science Training in Tambaram to Gain In-Demand Analytical Skills.
  • Data Science Certification Course with Job-Oriented Placement Assistance.
  • Flexible Data Science Training Schedules: Weekday, Weekend, and Fast-Track Batches.
  • Work on Real-Time Projects and Hands-On Tools with Expert Mentors.
  • Enhance Your Profile with Resume Building, Mock Interviews, and Career Support.
  • Includes Python, Statistics, Machine Learning, Tableau, and more from a Data Science training institute in Tambaram.

Course Duration

50+ Hrs

Live Project

3 Project

Certification Pass

Guaranteed

Training Format

Live Online (Expert Trainers)
WatchLive Classes
Course fee at
₹14500

₹18000

11875+

Professionals Trained

10+

Batches every month

3185+

Placed Students

258+

Corporate Served

What You'll Learn

Data Science Training in Tambaram offers comprehensive training in machine learning, data analysis, and data visualization techniques.

Develop skills in preprocessing and data cleaning for producing accurate insights and reliable prediction models.

Work with real-world datasets to gain hands-on experience with Python, R, and leading data science tools in Data Science Course in Tambaram.

Obtain real consumer analytics and business intelligence tools to support your data-driven decision-making.

Learn sophisticated methods for classification, regression, grouping, and recommendation systems.

Look into applying for internships in data science to further your career by getting real-world experience and exposure to the field.

An Overview of Data Science Course

Through the use of industry-standard tools and frameworks, Data Science Training in Tambaram has been thoughtfully designed to give students enhanced visualization skills, predictive analytics, and basic information manipulation abilities. The Data Science course curriculum provides a choice of learning alternatives that cater to a wide range of learning styles, including engaging instructor-led classes and easily accessible self-paced formats, all under the guidance of seasoned educators with real-world experience. This Data Science Certification Course in Tambaram is perfect for freshers and working professionals.Through in-depth case studies, real-world projects, and problem-solving activities, the comprehensive Data Science Training places a strong emphasis on practical experience. Your technical expertise and critical thinking abilities will be greatly enhanced by successfully completing this program, positioning you for a variety of in-demand positions in the domains of data science, business analytics, machine learning, and business intelligence. Enroll in our Data Science Course in Tambaram to build job-ready skills for real-world applications.

Future Trends for Data Science :

  • using more automated machine learning (AutoML is a) techniques for developing simpler models.
  • Explainable AI will be utilised more and more to validate and explain complex models in a clear manner.
  • bringing edge computing to real-time analysis of information close to the source.
  • extending AI-driven governance of information to guarantee moral and lawful data handling.
  • improved use of augmented analytics, which combines AI and conventional BI to provide deeper insights.
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Data Science Course Objectives

  • There is an extensive scope of Data Science with the technology development. Data science should appear as one of the several passionate career scopes. The current generation does observing a steep inclination towards data analytics, data science, including streams compared to computer science.
  • There is an extensive scope of Data Science with the technology development. Data science should appear as one of the several passionate career scopes. The current generation does observing a steep inclination towards data analytics, data science, including streams compared to computer science.
  • Prepare With Real-Time Problem Statement. Learning and mastering techniques remain mandatory, just to get the most famous out about your learning, you want to practice with real-time problem details you provide your data science procuring a quality.
  • Accept Reality.
  • Data science certificates are impossible to help greatly in your job demands, particularly at the initial pass/fail step of resume assessment, so you shouldn't concentrate on questions similar to "which data science certificate is best?" while you're trying to decide out wherever to think data science.
  • Data Scientist.
  • Machine Learning Engineer.
  • Machine Learning Scientist.
  • Applications Architect.
  • Enterprise Architect.
  • Data Architect.
  • Infrastructure Architect.
  • Data Engineer.
  • Statistics.
  • At least one programming language – R/ Python.
  • Data Extraction, Transformation, and Loading.
  • Data Wrangling and Data Exploration.
  • Machine Learning Algorithms.
  • Advanced Machine Learning (Deep Learning).
  • Big Data Processing Frameworks.
  • Data Visualization.
  • Data analysts are also no required to have excellent coding skills. Instead, they should own experience utilizing analytics software, data visualization software, including data management programs.
  • Introduction to Data Science and its importance
  • Data Science life cycle and data acquisition
  • Experimentation, evaluation, and project deployment tools
  • Various Machine Learning algorithms
  • Predictive analytics and segmentation using clustering
  • Fundamentals of Big Data Hadoop
  • Roles and responsibilities of a Data Scientist
  • Using real-world datasets to deploy recommender systems
  • Working on data mining and data manipulation
  • But based on our experience assisting people to transition in data science jobs, we understand it is reasonable to learn data science externally a computer science or mathematics experience. And further to take a job! So while you don't require a specific degree, you perform require the abilities.
  • It has now done listed as the hottest job, data scientist brings in professional sets and knowledge from different backgrounds such as mathematics, statistics, analytics, modeling, and business acumen. These skills help them to identify patterns that can increase the organizations recognizes new business possibilities.
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Benefits of Data Science Course

Data Science certification course in Tambaram offers a thorough and structured curriculum in addition to giving students worthwhile assignments that are meant to provide them a lot of real-world experience. Our curriculum will make it easy for you to transition into data science and analytics careers because it offers Data Science course with placement help and dedicated career support. You work on practical, business-related projects that help you develop a strong, visually appealing portfolio that effectively showcases your proficiency with data science and problem-solving methods.Get hands-on exposure through a guided Data Science internship in Tambaram, boosting your industry readiness.

  • Designation
  • Annual Salary
    Hiring Companies
  • 4.30L
    Min
  • 6.20L
    Average
  • 13L
    Max
  • 4L
    Min
  • 9.3L
    Average
  • 15.2L
    Max
  • 5.8L
    Min
  • 7.6L
    Average
  • 17.6L
    Max
  • 4.9L
    Min
  • 8.2L
    Average
  • 18.7L
    Max

About Your Data Science Training

With our Data Science Course in Tambaram, we provide thorough, approachable training in statistical modeling, machine learning, and data analysis. To increase your chances of getting hired, we connect you with a variety of hiring partners. Learn practical skills through real-world Data Science projects in Tambaram and case studies that will help you succeed in the competitive data science sector. Offering the best value for significant training and certification is the aim of the Data Science fees.

Top Skills You Will Gain
  • Data Wrangling
  • Predictive Modeling
  • Statistical Analysis
  • Machine Learning
  • Data Visualization
  • Programming Skills
  • Feature Engineering
  • Data Mining

12+ Data Science Tools

Online Classroom Batches Preferred

Weekdays (Mon - Fri)
06 - Oct - 2025
08:00 AM (IST)
Weekdays (Mon - Fri)
08 - Oct - 2025
08:00 AM (IST)
Weekend (Sat)
11 - Oct - 2025
11:00 AM (IST)
Weekend (Sun)
12 - Oct - 2025
11:00 AM (IST)
Can't find a batch you were looking for?
₹18000 ₹14500 10% OFF Expires in

No Interest Financing start at ₹ 5000 / month

Corporate Training

  • Customized Learning
  • Enterprise Grade Learning Management System (LMS)
  • 24x7 Support
  • Enterprise Grade Reporting

Why Data Science Course From Learnovita? 100% Money Back Guarantee

Data Science Course Curriculam

Trainers Profile

Experienced professionals in machine learning, statistical modeling, and data visualization teach our Data Science course in Tambaram. The program emphasizes experiential learning with real-world datasets and a wealth of training materials to guarantee simple concept comprehension. Students receive comprehensive instruction, earn a Data Science Certification, and acquire practical professional skills. Trainers provide individualized mentoring, interactive sessions, and continuous assistance throughout the course. As they improve their problem-solving skills, students work on real-world projects that replicate real-world challenges to increase their trust.

Syllabus for Data Science Training Download syllabus

  • What is Data Science, significance of Data Science in today’s digitally-driven world, applications of Data Science, lifecycle of Data Science, components of the Data Science lifecycle, introduction to big data and Hadoop, introduction to Machine Learning and Deep Learning, introduction to R programming and R Studio.
  • Hands-on Exercise - Installation of R Studio, implementing simple mathematical operations and logic using R operators, loops, if statements and switch cases.
  • Introduction to data exploration, importing and exporting data to/from external sources, what is data exploratory analysis, data importing, dataframes, working with dataframes, accessing individual elements, vectors and factors, operators, in-built functions, conditional, looping statements and user-defined functions, matrix, list and array.
  • Hands-on Exercise -Accessing individual elements of customer churn data, modifying and extracting the results from the dataset using user-defined functions in R.
  • Need for Data Manipulation, Introduction to dplyr package, Selecting one or more columns with select() function, Filtering out records on the basis of a condition with filter() function, Adding new columns with the mutate() function, Sampling & Counting with sample_n(), sample_frac() & count() functions, Getting summarized results with the summarise() function, Combining different functions with the pipe operator, Implementing sql like operations with sqldf.
  • Hands-on Exercise -Implementing dplyr to perform various operations for abstracting over how data is manipulated and stored.
  • Introduction to visualization, Different types of graphs, Introduction to grammar of graphics & ggplot2 package, Understanding categorical distribution with geom_bar() function, understanding numerical distribution with geom_hist() function, building frequency polygons with geom_freqpoly(), making a scatter-plot with geom_pont() function, multivariate analysis with geom_boxplot, univariate Analysis with Bar-plot, histogram and Density Plot, multivariate distribution, Bar-plots for categorical variables using geom_bar(), adding themes with the theme() layer, visualization with plotly package & building web applications with shinyR, frequency-plots with geom_freqpoly(), multivariate distribution with scatter-plots and smooth lines, continuous vs categorical with box-plots, subgrouping the plots, working with co-ordinates and themes to make the graphs more presentable, Intro to plotly & various plots, visualization with ggvis package, geographic visualization with ggmap(), building web applications with shinyR.
  • Hands-on Exercise -Creating data visualization to understand the customer churn ratio using charts using ggplot2, Plotly for importing and analyzing data into grids. You will visualize tenure, monthly charges, total charges and other individual columns by using the scatter plot.
  • Why do we need Statistics?, Categories of Statistics, Statistical Terminologies,Types of Data, Measures of Central Tendency, Measures of Spread, Correlation & Covariance,Standardization & Normalization,Probability & Types of Probability, Hypothesis Testing, Chi-Square testing, ANOVA, normal distribution, binary distribution.
  • Hands-on Exercise -– Building a statistical analysis model that uses quantifications, representations, experimental data for gathering, reviewing, analyzing and drawing conclusions from data.
  • Introduction to Machine Learning, introduction to Linear Regression, predictive modeling with Linear Regression, simple Linear and multiple Linear Regression, concepts and formulas, assumptions and residual diagnostics in Linear Regression, building simple linear model, predicting results and finding p-value, introduction to logistic regression, comparing linear regression and logistics regression, bivariate & multi-variate logistic regression, confusion matrix & accuracy of model, threshold evaluation with ROCR, Linear Regression concepts and detailed formulas, various assumptions of Linear Regression,residuals, qqnorm(), qqline(), understanding the fit of the model, building simple linear model, predicting results and finding p-value, understanding the summary results with Null Hypothesis, p-value & F-statistic, building linear models with multiple independent variables.
  • Hands-on Exercise -Modeling the relationship within the data using linear predictor functions. Implementing Linear & Logistics Regression in R by building model with ‘tenure’ as dependent variable and multiple independent variables.
  • Introduction to Logistic Regression, Logistic Regression Concepts, Linear vs Logistic regression, math behind Logistic Regression, detailed formulas, logit function and odds, Bi-variate logistic Regression, Poisson Regression, building simple “binomial” model and predicting result, confusion matrix and Accuracy, true positive rate, false positive rate, and confusion matrix for evaluating built model, threshold evaluation with ROCR, finding the right threshold by building the ROC plot, cross validation & multivariate logistic regression, building logistic models with multiple independent variables, real-life applications of Logistic Regression
  • Hands-on Exercise -Implementing predictive analytics by describing the data and explaining the relationship between one dependent binary variable and one or more binary variables. You will use glm() to build a model and use ‘Churn’ as the dependent variable.
  • What is classification and different classification techniques, introduction to Decision Tree, algorithm for decision tree induction, building a decision tree in R, creating a perfect Decision Tree, Confusion Matrix, Regression trees vs Classification trees, introduction to ensemble of trees and bagging, Random Forest concept, implementing Random Forest in R, what is Naive Bayes, Computing Probabilities, Impurity Function – Entropy, understand the concept of information gain for right split of node, Impurity Function – Information gain, understand the concept of Gini index for right split of node, Impurity Function – Gini index, understand the concept of Entropy for right split of node, overfitting & pruning, pre-pruning, post-pruning, cost-complexity pruning, pruning decision tree and predicting values, find the right no of trees and evaluate performance metrics.
  • Hands-on Exercise -Implementing Random Forest for both regression and classification problems. You will build a tree, prune it by using ‘churn’ as the dependent variable and build a Random Forest with the right number of trees, using ROCR for performance metrics.
  • What is Clustering & it’s Use Cases, what is K-means Clustering, what is Canopy Clustering, what is Hierarchical Clustering, introduction to Unsupervised Learning, feature extraction & clustering algorithms, k-means clustering algorithm, Theoretical aspects of k-means, and k-means process flow, K-means in R, implementing K-means on the data-set and finding the right no. of clusters using Scree-plot, hierarchical clustering & Dendogram, understand Hierarchical clustering, implement it in R and have a look at Dendograms, Principal Component Analysis, explanation of Principal Component Analysis in detail, PCA in R, implementing PCA in R.
  • Hands-on Exercise -Deploying unsupervised learning with R to achieve clustering and dimensionality reduction, K-means clustering for visualizing and interpreting results for the customer churn data
  • Introduction to association rule Mining & Market Basket Analysis, measures of Association Rule Mining: Support, Confidence, Lift, Apriori algorithm & implementing it in R, Introduction to Recommendation Engine, user-based collaborative filtering & Item-Based Collaborative Filtering, implementing Recommendation Engine in R, user-Based and item-Based, Recommendation Use-cases.
  • Hands-on Exercise -Deploying association analysis as a rule-based machine learning method, identifying strong rules discovered in databases with measures based on interesting discoveries.
  • Introducing Artificial Intelligence and Deep Learning, what is an Artificial Neural Network, TensorFlow – computational framework for building AI models, fundamentals of building ANN using TensorFlow, working with TensorFlow in R.
  • What is Time Series, techniques and applications, components of Time Series, moving average, smoothing techniques, exponential smoothing, univariate time series models, multivariate time series analysis, Arima model, Time Series in R, sentiment analysis in R (Twitter sentiment analysis), text analysis.
  • Hands-on Exercise -Analyzing time series data, sequence of measurements that follow a non-random order to identify the nature of phenomenon and to forecast the future values in the series.
  • Introduction to Support Vector Machine (SVM), Data classification using SVM, SVM Algorithms using Separable and Inseparable cases, Linear SVM for identifying margin hyperplane.
  • What is Bayes theorem, What is Naïve Bayes Classifier, Classification Workflow, How Naive Bayes classifier works, Classifier building in Scikit-learn, building a probabilistic classification model using Naïve Bayes, Zero Probability Problem.
  • Introduction to concepts of Text Mining, Text Mining use cases, understanding and manipulating text with ‘tm’ & ‘stringR’, Text Mining Algorithms, Quantification of Text, Term Frequency-Inverse Document Frequency (TF-IDF), After TF-IDF.
  • This case study is associated with the modeling technique of Market Basket Analysis where you will learn about loading of data, various techniques for plotting the items and running the algorithms. It includes finding out what are the items that go hand in hand and hence can be clubbed together. This is used for various real world scenarios like a supermarket shopping cart and so on.
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Industry Projects

Project 1
Fraud Detection System

Use anomaly detection and classification algorithms on transactional data to identify fraudulent activities. This project enhances security measures and protects company assets.

Project 2
Product Recommendation Engine

Implement collaborative filtering and content-based filtering techniques to suggest products tailored to customer preferences. This boosts sales and enhances user experience.

Project 3
Customer Segmentation

Apply clustering algorithms to group customers based on purchasing behavior and demographics. Businesses can then target each segment with personalized marketing campaigns.

Career Support

Our Hiring Partner

Exam & Data Science Certification

At LearnoVita, You Can Enroll in Either the instructor-led Data Science Online Course, Classroom Training or Online Self-Paced Training.



Data Science Online Training / Class Room:

  • Participate and Complete One batch of Data Science Course Course
  • Successful completion and evaluation of any one of the given projects

Data Science Online Self-learning:

  • Complete 85% of the Data Science Certification Training
  • Successful completion and evaluation of any one of the given projects
Honestly Yes, LearnoVita Provide 1 Set of Practice test as part of Your Data Science Certification Course in Tambaram. It helps you to prepare for the actual Data Science Certification Training exam. You can try this free Data Science Fundamentals Practice Test to Understand the Various type of tests that are Comes Under the Parts of Course Curriculum at LearnoVita.

These are the Different Kinds of Certification levels that was Structured under the Data Science Certification Path.

  • Certified Analytics Professional (CAP)
  • Cloudera Certified Associate: Data Analyst
  • Cloudera Certified Professional: CCP Data Engineer
  • Data Science Council of America (DASCA) Senior Data Scientist (SDS)
  • Data Science Council of America (DASCA) Principle Data Scientist (PDS)
  • Dell EMC Data Science Track
  • Google Certified Professional Data Engineer
  • Google Data and Machine Learning
  • IBM Data Science Professional Certificate
  • Microsoft MCSE: Data Management and Analytics
  • Microsoft Certified Azure Data Scientist Associate
  • Open Certified Data Scientist (Open CDS)
  • SAS Certified Advanced Analytics Professional
  • SAS Certified Big Data Professional
  • SAS Certified Data Scientist
  • Learn About the Certification Paths.
  • Write Code Daily This will help you develop Coding Reading and Writing ability.
  • Refer and Read Recommended Books Depending on Which Exam you are Going to Take up.
  • Join LernoVita Data Science Certification Training in Tambaram That Gives you a High Chance to interact with your Subject Expert Instructors and fellow Aspirants Preparing for Certifications.
  • Solve Sample Tests that would help you to Increase the Speed needed for attempting the exam and also helps for Agile Thinking.
Honestly Yes, Please refer to the link This Would Guide you with the Top 20 Interview Questions & Answers for Data Science Developers.

Our Student Successful Story

checkimage Regular 1:1 Mentorship From Industry Experts checkimage Live Classes checkimage Career Support

How are the Data Science Course with LearnoVita Different?

Feature

LearnoVita

Other Institutes

Affordable Fees

Competitive Pricing With Flexible Payment Options.

Higher Data Science Fees With Limited Payment Options.

Live Class From ( Industry Expert)

Well Experienced Trainer From a Relevant Field With Practical Data Science Training

Theoretical Class With Limited Practical

Updated Syllabus

Updated and Industry-relevant Data Science Course Curriculum With Hands-on Learning.

Outdated Curriculum With Limited Practical Training.

Hands-on projects

Real-world Data Science Projects With Live Case Studies and Collaboration With Companies.

Basic Projects With Limited Real-world Application.

Certification

Industry-recognized Data Science Certifications With Global Validity.

Basic Data Science Certifications With Limited Recognition.

Placement Support

Strong Placement Support With Tie-ups With Top Companies and Mock Interviews.

Basic Placement Support

Industry Partnerships

Strong Ties With Top Tech Companies for Internships and Placements

No Partnerships, Limited Opportunities

Batch Size

Small Batch Sizes for Personalized Attention.

Large Batch Sizes With Limited Individual Focus.

Additional Features

Lifetime Access to Data Science Course Materials, Alumni Network, and Hackathons.

No Additional Features or Perks.

Training Support

Dedicated Mentors, 24/7 Doubt Resolution, and Personalized Guidance.

Limited Mentor Support and No After-hours Assistance.

Data Science Course FAQ's

Certainly, you are welcome to join the demo session. However, due to our commitment to maintaining high-quality standards, we limit the number of participants in live sessions. Therefore, participation in a live class without enrollment is not feasible. If you're unable to attend, you can review our pre-recorded session featuring the same trainer. This will provide you with a comprehensive understanding of our class structure, instructor quality, and level of interaction.
All of our instructors are employed professionals in the industry who work for prestigious companies and have a minimum of 9 to 12 years of significant IT field experience. A great learning experience is provided by all of these knowledgeable people at LearnoVita.
  • LearnoVita is dedicated to assisting job seekers in seeking, connecting, and achieving success, while also ensuring employers are delighted with the ideal candidates.
  • Upon successful completion of a career course with LearnoVita, you may qualify for job placement assistance. We offer 100% placement assistance and maintain strong relationships with over 650 top MNCs.
  • Our Placement Cell aids students in securing interviews with major companies such as Oracle, HP, Wipro, Accenture, Google, IBM, Tech Mahindra, Amazon, CTS, TCS, Sports One , Infosys, MindTree, and MPhasis, among others.
  • LearnoVita has a legendary reputation for placing students, as evidenced by our Placed Students' List on our website. Last year alone, over 5400 students were placed in India and globally.
  • We conduct development sessions, including mock interviews and presentation skills training, to prepare students for challenging interview situations with confidence. With an 85% placement record, our Placement Cell continues to support you until you secure a position with a better MNC.
  • Please visit your student's portal for free access to job openings, study materials, videos, recorded sections, and top MNC interview questions.
LearnoVita Certification is awarded upon course completion and is recognized by all of the world's leading global corporations. LearnoVita are the exclusive authorized Oracle, Microsoft, Pearson Vue, and Data Science I exam centers, as well as an authorized partner of Data Science . Additionally, those who want to pass the National Authorized Certificate in a specialized IT domain can get assistance from LearnoVita's technical experts.
As part of the training program, LearnoVita provides you with the most recent, pertinent, and valuable real-world projects. Every program includes several projects that rigorously assess your knowledge, abilities, and real-world experience to ensure you are fully prepared for the workforce. Your abilities will be equivalent to six months of demanding industry experience once the tasks are completed.
At LearnoVita, participants can choose from instructor-led online training, self-paced training, classroom sessions, one-to-one training, fast-track programs, customized training, and online training options. Each mode is designed to provide flexibility and convenience to learners, allowing them to select the format that best suits their needs. With a range of training options available, participants can select the mode that aligns with their learning style, schedule, and career goals to excel in Data Science .
LearnoVita guarantees that you won't miss any topics or modules. You have three options to catch up: we'll reschedule classes to suit your schedule within the course duration, provide access to online class presentations and recordings, or allow you to attend the missed session in another live batch.
Please don't hesitate to reach out to us at contact@learnovita.com if you have any questions or need further clarification.
To enroll in the Data Science at LearnoVita, you can conveniently register through our website or visit any of our branches in India for direct assistance.
Yes, after you've enrolled, you will have lifetime access to the student portal's study materials, videos, and top MNC interview questions.
At LearnoVita, we prioritize individual attention for students, ensuring they can clarify doubts on complex topics and gain a richer understanding through interactions with instructors and peers. To facilitate this, we limit the size of each Data Science Service batch to 5 or 6 members.
The average annual salary for Data Science Professionals in India is 6 LPA to 7 LPA.
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