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Data Science Course in Chennai With Placement

(5.0) 8215 Ratings 8674Learners
100% Job Guarantee | Minimum CTC: ₹ 6 LPA

Our online data science course in Chennai offers hands-on experience. Participate in this IBM-sponsored data science course, which provides master courses, ask-me-anything sessions, and unique hackathons. Learn about Python, SQL, Excel, Tableau, Machine Learning, Generative AI, prompt engineering, ChatGPT, and other topics firsthand.

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  • 40+ Hrs Hands On Learning
  • 3+ Live Best Industry Projects
  • 25+ Practical Assignments
  • 24/7 Student Helpdesk

Online Classroom Batches Preferred

17- Jun- 2024
Monday (Monday - Friday)

Weekdays Regular

08:00 AM (IST)

(Class 1Hr - 1:30Hrs) / Per Session

12- May- 2024
Wednesday (Monday - Friday)

Weekdays Regular

08:00 AM (IST)

(Class 1Hr - 1:30Hrs) / Per Session

15- Jun- 2024
Saturday (Saturday - Sunday)

Weekend Regular

11:00 AM (IST)

(Class 3hr - 3:30Hrs) / Per Session

15- Jun- 2024
Saturday (Saturday - Sunday)

Weekend Fasttrack

11:00 AM (IST)

(Class 4:30Hr - 5:00Hrs) / Per Session

Can't find a batch you were looking for?
₹18000 ₹14500 10% OFF Expires in

No Interest Financing start at ₹ 5000 / month

A Comprehensive overview to the Data Science Course

A thorough online course on data science usually includes a broad range of subjects and abilities required to become an expert in the field. This includes an overview of data science and its applications across various industries. This aids in understanding the principles of machine learning algorithms, supervised and unsupervised learning techniques, model evaluation, validation, and hyperparameter tuning, introduction to neural networks and deep learning frameworks like TensorFlow or PyTorch.

Additional Info

Exploring Future Advancements in Data Science

  • Artificial Intelligence and Machine Learning: Data science will continue to be revolutionized by advances in AI and machine learning algorithms, which will make it possible to perform more complex reinforcement learning, natural language processing (NLP), computer vision, and predictive modeling. Breakthroughs in deep learning architectures, such as transformers and generative adversarial networks (GANs), will lead to more powerful and versatile AI models capable of handling complex and diverse datasets.
  • Big Data and Distributed Computing: Big data processing and analysis will place an increasing focus on scalable and distributed computing frameworks as the amount, velocity, and variety of data increase. Using distributed deep learning frameworks, Apache Spark, and Flink, among other technologies, enterprises will be able to quickly and efficiently extract insights from large datasets.
  • BI Developer: BI Developers design, develop, and maintain data warehouses and BI solutions. Your proficiency in database management systems, ETL processes, and BI tools will enable you to build robust data infrastructure and analytical solutions to support business operations.
  • Edge Computing and IoT Analytics: Real-time analytics at the edge and edge computing will receive more attention as Internet of Things (IoT) devices and sensors proliferate. Decentralized processing and analysis of IoT data will be made possible by data science techniques designed for edge devices, such as federated learning strategies and lightweight machine learning models. This will result in quicker insights and lower latency.
  • Hybrid Cloud: Hybrid cloud combines public and private cloud environments, allowing organizations to leverage the benefits of both. It provides flexibility, scalability, and control over sensitive data while utilizing public cloud resources for scalability and cost-efficiency.
  • Explainable AI and Responsible Data Science: There will be an increasing need for explainable AI (XAI) methods that offer interpretability and transparency in model predictions and decision-making procedures as AI systems become more commonplace. In order to ensure that AI systems meet ethical and legal requirements, responsible data science practices—such as ethical AI and fairness, accountability, and transparency (FAT) considerations—will be essential to their development and implementation.
  • Automated Machine Learning (AutoML): The democratization of machine learning through AutoML platforms will empower non-experts to build and deploy machine learning models with minimal manual intervention.AutoML tools will automate various aspects of the machine learning pipeline, including feature engineering, model selection, hyperparameter tuning, and model deployment, accelerating the development cycle and democratizing access to AI.
  • Domain-Specific Data Science Solutions: Industry-specific data science solutions tailored for domains such as healthcare, finance, retail, manufacturing, and energy will continue to emerge, addressing unique challenges and opportunities within each sector. These domain-specific solutions will leverage domain expertise, specialized datasets, and custom algorithms to deliver targeted insights and value-added analytics for specific use cases and applications.

Mastering Data Science: Essential Tools for Developers

  • Jupyter Notebook: Developers can create and share documents with live code, equations, visualizations, and narrative text in this web-based interactive computing environment. Jupyter Notebook is a popular application for data exploration and analysis that supports several computer languages, of which Python and R are just two examples.
  • Visual Studio Code (VS Code): A potent yet lightweight code editor with built-in support for R and Python, among other computer languages. Because it has features like code completion, syntax highlighting, and debugging, Visual Studio Code is a well-liked option for data science programming.
  • NumPy: NumPy is a core Python library for scientific computing that supports random number generation, mathematical functions, multidimensional arrays, and linear algebra operations.
  • Pandas: Pandas is a robust library for Python data manipulation and analysis that provides functions and data structures for effectively managing structured data, including data intake, cleaning, transformation, and exploration.
  • Matplotlib: With the help of Matplotlib, a feature-rich Python plotting package, programmers may design a large variety of static, interactive, and publication-quality visualizations, such as line, scatter, and bar charts.
  • Multi-cloud Strategy: A multi-cloud strategy involves utilizing services from multiple cloud providers to avoid vendor lock-in, optimize costs, mitigate risks, and leverage best-of-breed solutions. It requires robust management and orchestration capabilities to ensure interoperability and workload portability.
  • scikit-learn: Scikit-learn is a straightforward yet effective machine learning package for Python that provides a large range of tools and techniques for both supervised and unsupervised learning, such as dimensionality reduction, clustering, regression, classification, and model evaluation.
  • TensorFlow and PyTorch: Deep learning frameworks that let programmers create and train neural networks for a range of applications, such as reinforcement learning, natural language processing, and image classification.

Exploring Career Paths in Data Science

  • Data Scientist:As a data scientist, you will use your expertise in statistical modeling, machine learning, and data analysis to draw conclusions from data and resolve challenging business issues. Working with huge datasets, creating prediction models, and informing stakeholders of findings are all part of the job.
  • Data Analyst: The primary goal of data analysis and interpretation for data analysts is to find patterns, trends, and insights that can guide business choices. Their approach involves utilizing statistical methods, data visualization software, and subject expertise to convert data into meaningful insights.
  • DevOps Engineer: Integrates development and operations teams to streamline software delivery pipelines, leveraging cloud technologies for continuous integration, deployment, and monitoring to enhance agility and collaboration.
  • Machine Learning Engineer: In production settings, machine learning models and algorithms are designed, constructed, and implemented by machine learning engineers. Scalable and effective solutions for practical applications are created in close collaboration with data scientists and software engineers.
  • Business Intelligence Analyst: Business intelligence analysts assist firms in making decisions by gathering, analyzing, and presenting data. They create dashboards, reports, and visualizations that offer insights into company metrics and key performance indicators (KPIs).
  • Data Engineer: Data engineers focus on designing and maintaining data pipelines, databases, and infrastructure to support data-driven initiatives. They work with big data technologies, ETL (extract, transform, load) processes, and data warehousing solutions to ensure data availability and reliability.
  • AI Research Scientist: AI research scientists conduct research and development in the field of artificial intelligence (AI), exploring new algorithms, techniques, and methodologies to advance the state-of-the-art in machine learning and AI.
  • Quantitative Analyst (Quant): AQuants create models and strategies for trading, risk management, and investment analysis by applying mathematical and statistical techniques to financial data. Their areas of expertise include financial modeling, algorithmic trading, and quantitative finance.

Companies Looking for Data Science Professionals

  • Amazon: Amazon utilizes data science and machine learning across its e-commerce platform, cloud computing services (Amazon Web Services), digital content (Amazon Prime Video, Kindle), and logistics and supply chain operations. Its data scientists work on projects such as personalized recommendations, demand forecasting, and fraud detection.
  • Microsoft: Microsoft hires data scientists and analysts to work on projects related to Microsoft Azure, Office 365, Bing, and other products and services. Microsoft's data science professionals use machine learning and analytics to drive product innovation, improve user experiences, and solve complex problems.
  • Google: Google employs data scientists and machine learning engineers across various teams and departments, including Google AI, Google Cloud, and Google Research. Google data scientists work on projects ranging from search algorithms to natural language processing and computer vision.
  • Facebook: Facebook employs data scientists and machine learning engineers to analyze user data, improve content recommendations, enhance advertising targeting, and develop new features and products. Data science professionals at Facebook work on projects related to social network analysis, natural language processing, and computer vision.
  • Apple: Apple utilizes data science and analytics to improve user experiences across its products and services, including iPhone, iPad, Mac, Apple Watch, and Apple Music. Data scientists at Apple work on projects such as user behavior analysis, personalization, and optimization of algorithms.
  • Uber: Uber utilizes data science and analytics to optimize ride-hailing operations, improve driver and rider experiences, and develop new products and services. Its data scientists work on projects such as dynamic pricing, route optimization, and demand forecasting.
  • Airbnb: Airbnb employs data scientists and analysts to analyze user behavior, optimize search and booking experiences, and develop pricing strategies. Data science professionals at Airbnb work on projects related to user segmentation, market analysis, and recommendation systems.
  • General Electric (GE): General Electric utilizes data science and analytics to optimize operations across its various business units, including aviation, healthcare, power, and renewable energy. Data science professionals at GE work on projects related to predictive maintenance, asset optimization, and industrial IoT.
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Top Skills You Will Gain
  • R Programmming, Python, SAS
  • Artifical Intelligence
  • Deep Learning
  • Machine Learning
  • Statistics, Naive Bayes
  • Linear Algebra, CART
  • Programming, Neural Networks
  • Data Mining, Visualization

Data Science Course Key Features 100% Money Back Guarantee

  • 5 Weeks Training

    For Become a Expert
  • Certificate of Training

    From Industry Data Science Experts
  • Beginner Friendly

    No Prior Knowledge Required
  • Build 3+ Projects

    For Hands-on Practices
  • Lifetime Access

    To Self-placed Learning
  • Placement Assistance

    To Build Your Career

Top Companies Placement

Our Data science course explores your proficiency in data science concepts, techniques, and tools, providing tangible evidence of your skills to employers. Maximizes recruitment efforts and guarantees that companies discover proficient professionals in implementing and optimizing data analysis and its business techniques. Graduates can expect competitive compensation, with our placement support paving the way for substantial salary growth.
  • Designation
  • Annual Salary
    Hiring Companies
  • 4.7L
  • 7.9L
  • 16.7L
  • 5.10L
  • 8.3L
  • 17.1L
  • 4.52L
  • 8.3L
  • 17.2L
  • 4.9L
  • 8.2L
  • 18.0L

Training Options

Class Room Training

Talk to Placement Support

  • Exclusive one-on-one sessions for personalized skill development.
  • Latest version curriculum is provided by industrial professionals.
  • Get industry-recognized certification with placement assistance.
  • Lifetime Access to Study Materials, Videos & Top MNC Interview Question.
  • Work on multiple Industry-specific projects to enhance your portfolio.

Next Batch Schedule

17- Jun- 2024 (Weekdays Regular)

12- May- 2024 (Weekdays Regular)

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Online Training

₹18000₹ 14500

  • preferred
  • Schedule your sessions at your preferred timings for maximum convenience.
  • Lifetime access to high-quality self-learning and live online class recordings.
  • Attend a Free Demo before signing up.

Next Demo Sessions

show all batches

Corporate Training

Customized to your team's needs

  • Self-Paced/Live Online/Classroom modes of training available.
  • Design your own course content based on your project requirements.
  • Comprehensive certification guidance for your career advancement.
  • Get 100% Job-oriented Training With Dedicated Placement Support.
  • Receive 24x7 assistance and support to maximize your learning experience.

Self Paced Training

  • 50+ Hours High-quality Video
  • 28+ Downloadable Resource
  • Lifetime Access and 24x7 Support
  • Access on Your Computer or Mobile
  • Get Certificate on Course Completion
  • 3+ Projects
12500 ₹4500

Data Science Course Curriculum

Trainers Profile

At Learnovita, our data science course instructors are certified professionals who possess extensive industry expertise and are actively employed by reputable multinational firms. Committed to equipping learners with advanced knowledge and industry-standard practices in Data science, they ensure that students are well-prepared for success in today's competitive job market.

Syllabus of Data Science Online Certification Course in Chennai Download syllabus

  • Basics of Data Science
  • Application Significance
  • Python Overview
  • R Overview
  • Data Manipulation
  • SQL Fundamentals
  • Data Cleaning Methods
  • Preprocessing Techniques
  • Handling Missing Data
  • Data Normalization
  • Data Transformation
  • R and Python Libraries
  • EDA Concepts
  • Descriptive Statistics
  • Data Visualization Techniques
  • EDA with Python
  • EDA with R
  • Visualization Libraries
  • Probability Basics
  • Probability Distributions
  • Hypothesis Testing
  • Regression Analysis
  • R and Python Analysis
  • Machine Learning Overview
  • Evaluation Metrics
  • Supervised Learning
  • Unsupervised Learning
  • Hyperparameter Tuning
  • Feature Engineering
  • Advanced Techniques
  • Dimensionality Reduction
  • Deep Learning Basics
  • Gradient Boosting
  • Support Vector Machines
  • Decision Trees
  • TensorFlow Basics
  • Neural Networks
  • Building Networks
  • Convolutional Networks
  • Recurrent Networks
  • Transfer Learning
  • NLP Overview
  • Text Preprocessing
  • Sentiment Analysis
  • Word Embeddings
  • Text Classification
  • Named Entity Recognition
  • Big Data Introduction
  • Apache Hadoop
  • Apache Spark
  • Distributed Datasets
  • Spark MLlib
  • Machine Learning
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Need customized curriculum?

Industry Projects

Project 1
Industry-Specific Predictive Maintenance:

This project analyzes sensor data from industrial machinery using machine learning techniques to reduce downtime and operating expenses by seeing trends in the data that point to imminent failures.

Project 2
Sentiment Analysis of Social Media Data

This project entails applying natural language processing (NLP) techniques to analyze substantial amounts of social media data so that decision-makers can react quickly to new trends and make informed decisions.

Project 3
Customer Segmentation for Marketing Optimization

This project segments clients according to their demographics and purchasing patterns using clustering methods to know their distinct consumer segments, which will increase customer satisfaction.

Mock Interviews

  • Mock interviews by Learnovita give you the platform to prepare, practice and experience the real-life job interview. Familiarizing yourself with the interview environment beforehand in a relaxed and stress-free environment gives you an edge over your peers.
  • In our mock interviews will be conducted by industry best Data Science Course in Chennai experts with an average experience of 7+ years. So you’re sure to improve your chances of getting hired!

How Learnovita Mock Interview Works?

Data Science Training Objectives

Prerequisites for a Data Science course typically includes, Basic knowledge of R or Python, two programming languages, Familiarity with fundamental mathematical concepts such as statistics, linear algebra, and calculus, Some courses may also require prior knowledge of data analysis techniques and tools.
  • Programming Languages: Python, R, SQL
  • Data Manipulation and Analysis: pandas, NumPy.
  • Data Visualization: Matplotlib, Seaborn, ggplot2
  • Machine Learning: sci-kit-learn, TensorFlow, PyTorch
  • Big Data Processing: Apache Spark, Hadoop
Data science courses are becoming more and more important in today's job market due to the volume and complexity of data that businesses and organizations are producing at an increasing rate. Organizations in a range of industries need data science courses in order to stay competitive, learn new things, and make data-driven choices. This suggests that there is a high demand for data science courses as well as a wide range of career growth options.
  • Data Cleaning and Preprocessing
  • Exploratory Data Analysis
  • Statistical Analysis and Hypothesis Testing
  • Machine Learning Algorithms
  • Data Visualization Techniques
  • Big Data Processing and Distributed Computing
  • Natural Language Processing (NLP)
  • Deep Learning and Neural Networks
  • Model Evaluation and Validation
The future scope of data science courses is promising, with continued advancements in technology, data analytics, and artificial intelligence. Data science courses are expected to play an increasingly critical role in driving innovation, solving complex problems, and informing decision-making across various sectors, including healthcare, finance, retail, manufacturing, and beyond.
  • Proficiency with r or python as a programming language
  • Data manipulation and analysis skills using libraries like
  • pandas and numpy
  • Comprehension of statistical ideas and methods for data analysis
  • Understanding of predictive modeling methods and machine learning algorithms
  • Data visualization skills to communicate insights effectively
  • Problem-solving abilities and critical thinking skills
Yes, students work on real-world projects as part of our data science training program. These assignments give students actual experience and let them use their knowledge to address real-world issues with reliable data. Students who work on real-world projects develop a portfolio of work that shows prospective employers what they are capable of.
Learnovita's Data Science course may offer benefits such as
  • Comprehensive Curriculum
  • Hands On project
  • Expert Teachers
  • Job Placements
  • Flexible Learning Options
The certified data analysts are on high demand in various industries including technology, finance and banking, retail and e-commerce, manufacturing and supply chain, marketing and advertising.
  • Video lectures and tutorials covering various topics in data science.
  • Hands-on exercises and coding assignments to practice skills.
  • Reading materials such as textbooks, articles, and research papers.
  • Access to datasets for analysis and experimentation.
  • Support from instructors and mentors to assist with learning and project work.
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Exam & Certification

  • Vendor-specific Certifications
  • Professional Certifications
  • Academic Certifications
  • Specialized Certifications
  • Technology and IT analyst
  • Assistance with drugs and medical
  • Manager of financial services
  • Manufacturer of Digital commerce
  • Production manager for telecommunications analysis
Although earning a data science certification can improve your credentials and increase your marketability, employment is not guaranteed by it. On the other hand, if you can successfully showcase your abilities and knowledge during the employment process, a certification can greatly boost your chances of getting interviews and job offers.
Video lectures and tutorials covering various topics in data science, Hands-on exercises and coding assignments to practice skills, Reading materials such as textbooks, articles, and research papers, Access to datasets for analysis and experimentation, Support from instructors and mentors to assist with learning and project work.
Obtaining a Data Science certification can significantly enhance your career growth by opening up new job opportunities in the rapidly growing field of Data Science and keeping you updated with the latest advancements in cloud technologies through ongoing certification maintenance.

Recently Placed Students

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, HCL, 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. The National Institute of Education (NIE) in Singapore and LearnoVita are the exclusive authorized Oracle, Microsoft, Pearson Vue, and PSI exam centers, as well as an authorized partner of AWS. 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 Course 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 batch to 5 or 6 members.
The average annual salary for Data Science Professionals in India is 5 LPA to 8 LPA.
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