Beginner-Friendly Curriculum
You don't need to be an expert programmer to begin. The curriculum starts with programming, statistics, databases, and data fundamentals before progressing into machine learning and advanced topics.
Learn how to transform raw data into meaningful insights through a practical, industry-focused Data Science Course in Chennai. Build skills in Python, statistics, SQL, data visualization, machine learning, AI, and real-world data analysis through hands-on projects.
Whether you are a beginner, working professional, graduate, or aspiring data analyst, this program helps you progress from fundamental concepts to advanced data science techniques.
Learn. Analyse. Build. Solve real-world problems with data.
Choose a learning schedule that fits your professional or academic commitments.
| Batch Type | Suitable For | Schedule | Action |
|---|---|---|---|
| Weekday Batch | Students and professionals with flexible schedules | Flexible weekday sessions | Enroll Now |
| Weekend Batch | Working professionals and college students | Weekend sessions | Enroll Now |
| Online Batch | Learners who prefer remote learning | Flexible online sessions | Enroll Now |
| Offline Batch | Learners looking for classroom-based data science classes in Chennai | Contact for classroom schedule | Enroll Now |
Choosing the right training program is important when you are building a career in data. Codelyra focuses on practical learning rather than limiting the experience to theoretical concepts.
You don't need to be an expert programmer to begin. The curriculum starts with programming, statistics, databases, and data fundamentals before progressing into machine learning and advanced topics.
Work with realistic datasets and business scenarios to understand how data science is applied in real organizations.
Build practical programming skills with Python and learn widely used libraries and frameworks for data analysis, visualization, and machine learning.
The course introduces learners to machine learning and AI concepts, helping them understand how predictive models are created and evaluated.
Learn through practical demonstrations, guided exercises, assignments, and project discussions. Trainers should bring relevant industry experience and practical examples into the classroom.
Along with technical skills, learners can work on resume preparation, interview-oriented exercises, project discussions, and career guidance.
Build multiple projects that demonstrate your ability to clean data, analyse patterns, visualize information, and develop predictive models.
Choose weekday, weekend, online, or classroom learning options based on your schedule.
Codelyra provides placement-oriented support such as interview preparation, resume guidance, job-search assistance, and career guidance. Placement support does not guarantee employment, as hiring depends on individual skills, interview performance, experience, and employer requirements.
Our syllabus follows a beginner-to-advanced learning path, allowing learners to gradually build their technical and analytical capabilities.
By completing the Data Science Course in Chennai, learners can develop skills in:
A practical data science training in Chennai should expose learners to tools used across different stages of the data workflow.
Hands-on projects help learners connect concepts with practical business problems.
Objective: Predict customers who are likely to stop using an e-commerce platform.
Objective: Build a machine learning model to estimate property prices based on relevant features.
Objective: Group customers based on purchasing behaviour to support targeted marketing strategies.
Objective: Develop a predictive model that identifies patients belonging to different risk categories based on available data.
Objective: Analyse customer reviews and classify them according to sentiment.
Objective: Analyse historical sales data and develop a forecasting solution to support business planning.
Build practical data science skills through flexible learning options, certifications, career-oriented support, and industry-relevant projects.
Choose learning schedules designed to accommodate students, professionals, and career switchers.
Receive course-related certification opportunities based on the program structure and successful completion requirements. Third-party professional certifications, where applicable, may have separate eligibility or examination requirements.
Flexible EMI options may be available to make professional training more manageable. Contact Codelyra for the latest eligibility and payment details.
Get career-oriented assistance including resume guidance, interview preparation, job-search support, and career counselling. Placement support is intended to improve employability and does not guarantee a job offer.
Build practical projects around e-commerce, healthcare, retail, forecasting, customer analytics, and NLP to strengthen your portfolio.
The course can be suitable for learners from different educational, technical, and professional backgrounds who want to build practical data science skills.
Whether you are beginning your data science journey, advancing your current career, or planning a transition into analytics, the course provides a structured path toward practical data science.
Basic computer knowledge and an interest in analytical problem-solving are helpful. Programming experience is useful but not mandatory for beginners.
Find answers to common questions about the Data Science course, curriculum, programming, machine learning, projects, certification, placement support, and learning options.
A Data Science course teaches learners how to collect, clean, analyse, visualize, and model data to generate useful insights and support data-driven decisions. A comprehensive program generally covers Python, SQL, statistics, machine learning, visualization, and practical projects.
Yes. A beginner-friendly learning path starts with Python, SQL, statistics, and data fundamentals before progressing to machine learning, AI, and advanced data science concepts.
The course primarily focuses on Python, with exposure to R programming for data analysis and statistics.
Python is one of the most widely used programming languages in data science. Learning Python helps you work with datasets, perform analysis, visualize information, build machine learning models, and automate data workflows.
Yes. The curriculum progresses from data analysis and statistics to supervised learning, unsupervised learning, feature engineering, model evaluation, and advanced machine learning concepts.
Yes. The curriculum introduces AI concepts and their relationship with Data Science and Machine Learning, along with practical AI-oriented use cases.
Certification depends on the course completion requirements and certification structure. Learners should verify whether a certificate is an institute-issued course completion certificate or an external professional certification.
Data Analytics primarily focuses on examining existing data to identify trends, patterns, and insights. Data Science covers analytics along with programming, statistics, machine learning, predictive modelling, and more advanced data-driven applications.
Codelyra provides placement-oriented support such as resume preparation, interview training, career guidance, and job-search assistance. Placement support does not guarantee employment.
Yes. Python is a major part of the curriculum, covering programming fundamentals, Pandas, NumPy, visualization, data preprocessing, machine learning, and practical projects.
Yes. The curriculum includes R programming fundamentals and its application in data analysis, statistics, and visualization.
Depending on the current curriculum, learners can work with Python, R, SQL, Jupyter Notebook, Google Colab, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, Power BI, Tableau, Git, GitHub, and deployment tools.
The program includes multiple practical exercises and 6 industry-relevant capstone projects covering areas such as customer analytics, retail, healthcare, NLP, prediction, and forecasting.
Depending on skills, experience, and specialization, learners can explore roles such as:
Fees vary between institutes and depend on factors such as course duration, delivery mode, curriculum, projects, certifications, and placement support. Contact Codelyra for the latest course fee details.
The learning time depends on your existing programming knowledge, study schedule, course depth, and practice. A structured beginner-to-advanced program can help you learn progressively through guided lessons and projects.
A structured Data Science institute in Chennai can provide guided learning, trainer interaction, practical projects, peer learning, career preparation, and a clear progression from fundamentals to advanced concepts.
Online learning options may be available depending on the current batch schedule. Contact Codelyra to check the latest online and classroom options.
Weekend batches may be available for working professionals and students. Check with Codelyra for current schedules and availability.