Benefits of Learning Data Science
Learning Data Science offers numerous career benefits, including access to high-demand job opportunities and the ability to enhance problem-solving skills. By mastering data analytics and machine learning techniques, you can make data-driven decisions that help drive business innovation. With the growing reliance on data in every industry, learning Data Science positions you for success and provides a competitive edge in the job market.
Why learn Data Science from Cokonet?
Available Certifications
Hear it from our Alumni
"As a beginner, this course gave me a strong foundation in data science. The curriculum was comprehensive, and the practical focus helped me land a data science role after completing the course."
Anjali VS — Software Engineer
Why Cokonet?
Cokonet Academy offers expert-led Data Science training in Kerala with placement assistance, flexible fees, and industry experience, ensuring practical learning and career success.
Cokonet Academy offers placement assistance through partnerships with leading companies.
Cokonet Academy offers internship assistance to help students develop essential skills.
Cokonet Academy offers interest free loans for students in need.
Cokonet Academy offers flexible EMI payments to ease financial burdens.
Cokonet's Industry-Aligned Syllabus equips students with relevant skills and hands-on experience for career growth.
Experienced instructors at Cokonet guide learners through data science tools & technology, ensuring career success.
Cokonet’s global alumni network connects you to top MNCs.
With a 15-year legacy, Cokonet has been empowering students with industry-relevant skills and fostering career growth.
Data Science Course
Cokonet Academy
Data Science with AI
This comprehensive course equips learners with Python programming, NumPy, Pandas, and Matplotlib for data manipulation and visualization. Dive into machine learning, deep learning, NLP, and computer vision. Master Azure for MLOps to deploy and manage ML models. Prepare for a data science career with hands-on projects and real-world skills.
starts on
Jan 27, 2025
ELIGIBILITY
mode
Online
Still Confused?
Find the answers to frequently asked questions by our learners. If you have more questions, feel free to reach out to us.
Advanced Data Science goes beyond basic data analysis by incorporating cutting-edge techniques like deep learning, reinforcement learning, and generative AI. It focuses on creating predictive and prescriptive models, while traditional Data Science mainly involves descriptive and diagnostic analytics.
MLOps (Machine Learning Operations) bridges the gap between machine learning development and deployment. It ensures scalable, reliable, and efficient model management. By automating workflows and monitoring models in production, MLOps accelerates the delivery of AI solutions while maintaining quality.
Essential skills include programming (Python, R), data manipulation (SQL, Pandas), machine learning, model deployment, cloud computing, and proficiency in MLOps tools like Kubernetes, Docker, and TensorFlow Extended (TFX). Knowledge of CI/CD pipelines is also critical.
Career paths include Data Scientist, Machine Learning Engineer, MLOps Engineer, AI Specialist, and Cloud AI Architect. These roles are in high demand across industries like finance, healthcare, retail, and technology.
MLOps expertise is highly sought after as companies strive to streamline AI model deployment and maintenance. It makes you a valuable asset by combining machine learning knowledge with software engineering and DevOps, increasing employability and salary prospects.
Google’s MLOps Specialization AWS Certified Machine Learning – Specialty
No, a degree is not mandatory. Many professionals enter MLOps through bootcamps, online certifications, and hands-on projects. Practical experience and a strong portfolio often outweigh formal degrees.
Industries like healthcare, e-commerce, banking, automotive, and logistics are heavily investing in AI and MLOps to enhance automation, optimize processes, and gain a competitive edge.
Salaries in India vary by experience and skill level: Data Scientists earn ₹6,00,000–₹12,00,000 per year for entry-level positions and ₹15,00,000–₹25,00,000 per year for experienced roles. MLOps Engineers typically earn ₹8,00,000–₹16,00,000 per year for beginners and can go up to ₹30,00,000 or more for senior positions. Specialized skills in MLOps can significantly boost earning potential due to its high demand in the Indian job market.
Transitioning to Data Science and AI with MLOps from a non-technical background is achievable through structured learning. Start with the basics of Python, statistics, and machine learning. Enroll in beginner-friendly courses or bootcamps, and work on real-world projects to build a portfolio. Networking with industry professionals and earning certifications like Google’s MLOps Specialization or AWS Certified Machine Learning can accelerate your transition.
Your portfolio should showcase end-to-end projects, including data preprocessing, building and training machine learning models, deploying them using tools like Docker or Kubernetes, and implementing CI/CD pipelines for automation. Real-world examples, such as sentiment analysis or predictive analytics, demonstrate your ability to handle production-ready implementations effectively.
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