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Data Science Online Training in Ahmedabad

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  • Master Data Science Methodologies and Agile Frameworks with the Leading Data Science Online Course in Ahmedabad.
  • Includes Python, R, Machine Learning, Deep Learning, Data Visualization, and Big Data Analytics.
  • Data Science Certification Course Offering Career-Oriented Placement Support.
  • Flexible Data Science Training Schedules: Weekday, Weekend, or Fast-Track Online Options.
  • Gain Hands-On Experience with Real-Time Projects and Practical Sessions from Certified Data Science Trainers.
  • Receive Assistance with Resume Building, Mock Interviews, and Career Growth in Data Science Roles.

Course Duration

Hrs

Live Project

Project

Certification Pass

Guaranteed

Training Format

Live Online (Expert Trainers)
Quality Training With Affordable Fee

⭐ Fees Starts From

INR 38,000
INR 18,500

Professionals Trained

Batches every month

Placed Students

Corporate Served

What You'll Learn

This Data Science Online Training teaches essential data science concepts, ideal for both beginners and professionals.

Learn Data Science Online Course, covering Python, R, Machine Learning, and Big Data to strengthen analytical skills.

Explore data science principles such as data preprocessing, modeling, visualization, and predictive analytics.

Gain practical experience in real-time data science projects, including data analysis, machine learning models, and dashboards.

Advance from basic to expert-level data science skills for more effective decision-making and problem-solving.

Acquire the tools to apply data science frameworks and achieve certification to enhance your career prospects in Ahmedabad.

Comprehensive Overview of Data Science Course

The Data Science Online Training in Ahmedabad is designed to provide in-depth knowledge of data science methodologies, focusing on frameworks and tools like Python, R, Machine Learning, Deep Learning, Data Visualization, and Big Data Analytics. This training enhances analytical and problem-solving skills, enabling professionals to handle complex data projects efficiently with better insights, adaptability, and accuracy. Learners gain hands-on experience through real-world datasets, industry case studies, and guidance from certified data science experts. The course is offered in flexible formats, including self-paced and instructor-led sessions, to suit different learning needs. Completing Data Science Online Training strengthens your analytical expertise and boosts your career readiness, making you highly valuable to employers seeking Data Science professionals.

Additional Info

Upcoming Future Transformations in Data Science Online Training

  • Integration of AI and Automation: The future of Data Science Online Training is shifting towards AI-driven analytics and automation. Organizations increasingly rely on AI models and automated pipelines to process large datasets. Professionals trained in both traditional analytics and AI-enhanced methods will be in high demand to implement advanced solutions.
  • Data Science Across Industries: Data Science is expanding beyond IT into healthcare, finance, retail, and manufacturing. This growth is driven by the need for predictive insights, process optimization, and data-driven decision-making. Training prepares professionals to apply analytics and machine learning in diverse sectors.
  • Data Science for Remote and Distributed Teams: With remote work becoming common, Data Science methodologies are adapting for virtual collaboration. Cloud-based tools, collaborative notebooks, and online dashboards are increasingly standard. Training emphasizes best practices for working efficiently in distributed teams.
  • Integration with DevOps and MLOps: The convergence of data science with DevOps (MLOps) is a key trend. Continuous integration, deployment, and model monitoring are essential for production-ready AI. Training programs now incorporate MLOps concepts, preparing learners for end-to-end data science workflows.
  • Coaching & Mentoring in Data Science: As organizations adopt data-driven strategies, the demand for skilled data science mentors and coaches is increasing. Training programs emphasize developing mentorship skills and leadership in analytics teams.
  • Tools and Automation Integration: Data Science training increasingly includes integration with automation tools like Apache Airflow, MLflow, and DataRobot to streamline workflows. Training programs focus on combining analytics with automation for higher efficiency.
  • Scaling Data Science Practices: Scaling analytics for large enterprises is a growing trend, using frameworks like DataOps and enterprise AI. Training programs emphasize managing large-scale projects and collaborating across multiple teams.
  • Focus on Metrics and Analytics: Data-driven decision-making is central to Data Science. Training emphasizes using metrics, dashboards, and KPIs to measure performance and optimize models. Professionals need proficiency in interpreting and acting on insights from data.
  • Data Science for Product Management: Product teams adopt analytics to enhance product strategy and customer insights. Training covers integrating data science into product lifecycle management, helping professionals collaborate effectively with stakeholders.
  • Continuous Learning and Certifications: Data Science emphasizes ongoing learning and certification. Staying current with Python, R, Machine Learning, Deep Learning, and AI tools is critical. Specialized certifications give professionals a competitive advantage and drive career growth.

Building Tools and Techniques with Data Science Online Training

  • Python: Python is a core programming language in Data Science for data manipulation, analysis, and machine learning. Training covers libraries like Pandas, NumPy, Scikit-learn, and TensorFlow for practical applications.
  • R: R is a statistical programming language widely used for data analysis and visualization. Training includes data cleaning, statistical modeling, and creating insightful visualizations using ggplot2 and Shiny.
  • Jupyter Notebooks: Jupyter Notebooks provide an interactive environment for writing code, analyzing datasets, and visualizing results. Training covers collaborative notebooks for team projects.
  • Tableau: Tableau is a leading data visualization tool. Professionals learn to create dashboards, charts, and interactive reports for business insights.
  • Power BI: Power BI helps in business analytics and reporting. Training covers data modeling, creating visuals, and sharing insights with stakeholders.
  • SQL: SQL is essential for querying relational databases. Training covers joins, subqueries, and aggregations for data extraction and analysis.
  • Apache Spark: Spark is used for big data processing. Training includes distributed data processing, Spark SQL, and machine learning pipelines.
  • GitHub: GitHub supports version control and collaboration on data science projects. Training covers repository management, branching, and pull requests for teamwork.
  • Slack: Slack facilitates real-time team communication, integration with tools like Jupyter, GitHub, and Tableau for collaborative data science projects.
  • Azure / AWS Cloud: Cloud platforms provide scalable infrastructure for big data and machine learning. Training covers deployment, data storage, and cloud-based analytics solutions.

Roles and Responsibilities in Data Science

  • Data Scientist: Analyze data, build predictive models, and extract insights to drive business decisions. Collaborates with stakeholders to implement machine learning solutions and interpret results.
  • Data Analyst: Collect, clean, and visualize data to identify trends. Supports decision-making with actionable insights and dashboards.
  • Machine Learning Engineer: Designs, builds, and deploys machine learning models. Works closely with data scientists and engineers for scalable solutions.
  • Data Engineer: Develops and maintains data pipelines and architectures. Ensures data quality, reliability, and accessibility for analytics.
  • Business Analyst: Bridges the gap between business and technical teams. Defines requirements, interprets data, and ensures analytical solutions align with business goals.
  • AI/ML Researcher: Explores advanced algorithms, AI techniques, and research in machine learning to improve models and predictive capabilities.
  • Data Architect: Designs and manages large-scale data storage and processing systems. Ensures data governance and security compliance.
  • Project Manager: Oversees analytics projects, manages timelines, resources, and ensures delivery of insights in alignment with business objectives.

Top Companies Hiring for Data Science Professionals

  • Accenture: Hires data science professionals to implement AI, analytics, and machine learning solutions across industries.
  • Capgemini: Seeks data scientists and analysts for business analytics, predictive modeling, and data-driven decision-making projects.
  • Cognizant: Employs data science experts for AI initiatives, automation, and analytics solutions for global clients.
  • Tata Consultancy Services (TCS): Engages data scientists in enterprise analytics, AI model development, and big data solutions.
  • Infosys: Hires professionals to deliver analytics, machine learning, and AI-driven insights for business growth.
  • Wipro: Focuses on AI, data engineering, and advanced analytics projects for enterprise clients.
  • IBM: Seeks data science experts for AI research, cloud analytics, and machine learning solutions.
  • DXC Technology: Employs data professionals for big data, predictive analytics, and AI-enabled enterprise solutions.
  • SAP: Requires data scientists to enhance business intelligence, predictive modeling, and analytics-driven decision-making.
  • Amazon Web Services (AWS): Hires data professionals to build scalable AI and analytics solutions on cloud platforms.
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Data Science Course Objectives

Data Science training enables participants to build essential skills in data analysis, machine learning, and statistical modeling. Learners gain practical expertise in handling datasets, developing predictive models, and deriving actionable insights to support data-driven decision-making in organizations.
Data Science training is highly valued by employers as organizations across industries increasingly rely on data-driven insights. Professionals skilled in analytics, machine learning, and visualization are in high demand to improve business outcomes, making this training crucial for career advancement.
The future of Data Science training is very promising, with growing adoption across sectors like IT, finance, healthcare, retail, and manufacturing. Data Science expertise is critical for organizations to make informed decisions, implement AI-driven solutions, and stay competitive in evolving markets.
  • Basic understanding of statistics, mathematics, or programming.
  • Familiarity with data handling, problem-solving, and analytical thinking.
  • No prior experience in Data Science is required.
  • Willingness to learn programming languages like Python or R and work with datasets.
Yes, Data Science Online Training includes real-world projects to provide practical experience. These projects involve datasets from domains like finance, healthcare, and retail, allowing learners to implement analytics, machine learning models, and visualization techniques for hands-on learning.
  • Introduction to Data Science and Analytics
  • Python and R for Data Analysis
  • Statistics and Probability for Data Science
  • Machine Learning Algorithms and Model Building
  • Data Visualization with Tableau, Power BI, or Matplotlib
  • Big Data and Cloud Analytics
The Data Science Online Training program provides placement assistance, including guidance on resume building, interview preparation, and connecting with companies looking for skilled data professionals. Completing the training equips learners with the skills needed to secure roles in analytics and machine learning.
  • Information Technology and Software Development
  • Healthcare and Pharmaceuticals
  • Finance, Banking, and Insurance
  • Retail, E-commerce, and Marketing
  • Manufacturing, Logistics, and Supply Chain
Data Science certification validates expertise in analytics, machine learning, and data-driven decision-making. Certified professionals are recognized for their ability to extract insights from data, build predictive models, and contribute effectively to business strategy, making them highly sought after in the job market.
  • Python and R
  • Jupyter Notebook
  • Tableau and Power BI
  • SQL and NoSQL Databases
  • Big Data Tools: Apache Spark, Hadoop
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Benefits of Data Science Course

The Data Science Online Training, combined with a practical Data Science Internship, provides hands-on experience with Python, R, Machine Learning, and AI frameworks. Work on real-world projects under expert guidance and gain practical knowledge to prepare for high-paying roles in top organizations. Flexible course formats and pricing options are available, with guaranteed placement support.

  • Designation
  • Annual Salary
    Hiring Companies
  • 3.0L
    Min
  • 6.0L
    Average
  • 10.0L
    Max
  • Google
  • Microsoft
  • IBM
  • Amazon
  • 6.0L
    Min
  • 12.0L
    Average
  • 25.0L
    Max
  • Google
  • Microsoft
  • IBM
  • Amazon
  • 8.0L
    Min
  • 15.0L
    Average
  • 30.0L
    Max
  • Google
  • IBM
  • Amazon
  • Microsoft
  • 10.0L
    Min
  • 20.0L
    Average
  • 40.0L
    Max
  • Google
  • Microsoft
  • Amazon
  • IBM

About Your Data Science Online Training

Our Data Science Online Training provides a complete understanding of Data Science concepts, including Python, R, Machine Learning, and AI frameworks, equipping learners with practical expertise. The program offers hands-on experience through real-world Data Science projects, enabling participants to apply data-driven solutions in professional settings. With a blend of live instructor-led sessions, self-paced learning, and interactive exercises, students gain the essential skills to excel in data analysis, predictive modeling, and advanced analytics, advancing their careers in top organizations.

Top Skills You Will Gain
  • Sprint Planning
  • Backlog Management
  • Kanban & Scrum
  • User Stories
  • Continuous Improvement
  • Agile Collaboration
  • Mulesoft Coaching

12+ Mulesoft Tools

Online Classroom Batches Preferred

Weekdays (Mon - Fri)
13 - Apr - 2026
08:00 AM (IST)
Weekdays (Mon - Fri)
15 - Apr - 2026
08:00 AM (IST)
Weekend (Sat)
18 - Apr - 2026
11:00 AM (IST)
Weekend (Sun)
19 - Apr - 2026
11:00 AM (IST)
Can't find a batch you were looking for?
₹38,000 ₹18,500 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

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We’re Doing Much More!

Empowering Learning Through Real Experiences and Innovation

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Data Science Course Curriculam

Trainers Profile

LearnoVita is filled with the best and top MNC trainers +11 years of highly experienced professionals. As all Trainers are working professionals so they are having many live projects , trainers will use these projects during training sessions . Our trainer will give you technical supports and passionate about data and data-driven decision making.

Syllabus of Data Science Course in Ahmedabad 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
Predictive Analytics for E-commerce

Develop a predictive analytics model to forecast customer behavior and sales trends in an e-commerce platform using real datasets, Python, and machine learning algorithms.

Project 2
Healthcare Data Analysis & Dashboard

Analyze healthcare datasets to extract actionable insights, implement visualizations using Tableau or Python libraries, and build interactive dashboards for informed decision-making.

Project 3
Customer Segmentation & Recommendation System

Use clustering and machine learning techniques to segment customers and develop a recommendation system that enhances personalization and boosts engagement.

Our Hiring Partner

Exam & 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 Online 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 Ahmedabad. 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 Ahmedabad 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 learners
transformed their careers

35 Laks
Highest Salary Offered
50%
Average Salary Hike
30K+
Placed in MNC's
15+
Year's in Training
Our Alumni
Alumni

A majority of our alumni

fast-tracked into managerial careers.

Get inspired by their progress in the Career Growth Report.

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Data Science Online Course FAQ's

LearnoVita Offers a good discount percentage for you CALL at +91 93833 99991 and know the Exciting offers Available for you!!!
Yes, you can attend the demo session. Even though We have a limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrolment is not possible.If you are unable to attend you can go through our Pre recorded session of the same trainer, it would give you a clear insight about how the classes are conducted, the quality of instructors, and the level of interaction in the class.
All Our instructors from Data Science Classes in Ahmedabad are working professionals from the Industries, Working in leading Organizations and have Real-World Experience with Minimum 9-12 yrs of Relevant IT field Experience. All these experienced folks at LearnoVita Provide a Great learning experience.
The trainer will give Server Access to the course seekers, and we make sure you acquire practical hands-on training by providing you with every utility that is needed for your understanding of the course
  • LearnoVita Best Data Science Online Course in Ahmedabad will assist the job seekers to Seek, Connect & Succeed and delight the employers with the perfect candidates.
  • On Successfully Completing a Career Course from LearnoVita Best Data Science Online Course in Ahmedabad, you Could be Eligible for Job Placement Assistance.
  • 100% Placement Assistance* - We have strong relationship with over 650+ Top MNCs, When a student completes his/ her course successfully, LearnoVita Placement Cell helps him/ her interview with Major Companies like Oracle, HP, Wipro, Accenture, Google, IBM, Tech Mahindra, Amazon, CTS, TCS, HCL, Infosys, MindTree and MPhasis etc...
  • LearnoVita is the Legend in offering placement to the students. Please visit our Placed Students's List on our website.
  • More than 5400+ students placed in last year in India & Globally.
  • LearnoVita is the Best Data Science Online Course Institute in Ahmedabad Offers mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student's Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
After Your Course Completion You will Receive
  • LearnoVita Certification is Accredited by all major Global Companies around the World.
  • LearnoVita is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of Data Science and National Institute of Education (nie) Singapore
  • Also, LearnoVita Technical Experts Help's People Who Want to Clear the National Authorized Certificate in Specialized IT Domain.
  • LearnoVita is offering you the most updated Data Science certification training in Ahmedabad, relevant, and high-value real-world projects as part of the training program.
  • All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
  • You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc.
  • After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.
At LearnoVita you can enroll in either the instructor-led Data Science Online Course, Self-Paced Training, Class Room, One to One Training, Fast Track, Customized Training & Online Training Mode. Apart from this, LearnoVita also offers Corporate Training for organizations to UPSKILL their workforce.
LearnoVita Assures You will Never lose any Topics and Modules. You can choose either of the Three options:
  • We will reschedule the Data Science classes in Ahmedabad as per your convenience within the stipulated course duration with all such possibilities.
  • View the class presentation and recordings that are available for online viewing.
  • You can attend the missed session, in any other live batch.
Just give us a CALL at +91 9383399991 OR email at contact@learnovita.com
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question After Once You Have Enrolled.
We at LearnoVita believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics and Can Access more information and Richer Understanding through teacher and other students' body language and voice. Therefore, we restrict the size of each Data Science batch to 5 or 6 members
Learning Data Science can help open up many opportunities for your career. It is a GREAT SKILL-SET to have as many developer roles in the job market requires proficiency in Data Science. Mastering Data Science can help you get started with your career in IT. Companies like Oracle, IBM, Wipro, HP, HCL, DELL, Bosch, Capgemini, Accenture, Mphasis, Paypal, and MindLabs.
The Average salary of Data Science Developer in India is ₹4,43,568 per annum.
You can contact our support number at +91 93800 99996 / Directly can do by LearnoVita E-commerce payment system Login or directly walk-in to one of the LearnoVita branches in India.
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