SP
background

👋 I'm Senthil Palanivelu 

I’m a Computer Science professional with a background in Data Analytics, AI Engineering, and Machine Learning. I enjoy exploring data to uncover patterns and trends that drive informed decision-making. My goal is to leverage AI and data-driven insights to solve real-world challenges and deliver clear, measurable value to businesses.

Resume
Senthil Palanivelu

Education

  • Master of Science in Computer Science

    Jan 2015 - Jan 2019 | University of Massachusetts Boston | USA

    Courses: Advanced Algorithms, Algorithms in Bioinformatics, Analysis of Algorithm, Big Data Analytics, Linear Algebra, Calculus, Software Development and Design, Database Management, Computing Data Structure, Mathematical Logic

  • Bachelor of Engineering in Electronics and Communication

    Sep 2007 - Sep 2011 | Anna University | India

    Courses: Signal Processing, Microprocessor, Satellite communication, Control Systems Design

  • Certifications

  • Mathematics for Machine Learning and Data Science

    July 2024 | DeepLearning.AI on Coursera

    A comprehensive course covering fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

    View Certificate

  • Google Prompting Essentials

    February 2025 | Google on Coursera

    AI agent design, Multimodal prompting, Prompt chaining, Prompt Design, Prompt evaluation and iteration, Responsible AI.

    View Certificate

  • Supervised Machine Learning: Regression and Classification

    March 2025 | DeepLearning.AI on Coursera | Standford Online

    Build & train supervised machine learning models in Python using popular libraries NumPy & scikit-learn for prediction & binary classification tasks, including linear regression & logistic regression.

    View Certificate

Skills

  • Languages

    PythonR ProgrammingR ShinySQLJavaScriptTypeScriptHTMLCSSShell ScriptingMATLAB

  • Full Stack Development

    Next.jsReactTailwind CSSFramer MotionZustandNode.jsREST APIsStreamlitFastAPI

  • Machine Learning & AI

    Machine LearningDeep LearningLLMs & RAGAI AgentsComputer VisionNLPPyTorchScikit-learnXGBoostOpenAI APIPrompt EngineeringRandom ForestSVMGradient DescentPCANeural Networks

  • Data Science & Analytics

    Data AnalysisStatistical ModelingHypothesis TestingTime Series AnalysisSignal ProcessingBayesian StatisticsPandasNumPyMatplotlib/SeabornData VisualizationLinear/Logistic RegressionProbability Theory

  • Tools & Platforms

    AWSDockerLinuxGit/GitHubCI/CDGitHub ActionsVS CodeJupyterNetlifyPyMuPDFPinecone