Pavan AI/ML, Statistics, Mathematics
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Hi I am Pavan, I have completed my master in statistics and specialized in Data science.

National eligibility test (UGC - NET) qualified in statistics for teaching.
Strong statistics knowledge: Sampling, Time series Analysis, Multivariate Analysis, Design of Experiment, Statistical inference, mathematical statistics, Biostatistics.

Strong programming skill : Python, R, Databricks and SQL
Teaching mode : Online.
Teaching style : ppt/article/programming using python or R.
Current profession : Associate professor. Dept of statistics, at Agricultural college.

Assignment completed : Machine learning based industry projects and computer vision, Master and PhD level statistical Analysis, Analysis for Research publication for Agricultural and medical science, Data visualization/chart/Graphs preparation Research article/Thesis/conference, Econometrics, operations research and other.
Taught Statistics and Applied Probability to engineering and data science students with a strong focus on real-world applications.

Major courses for teaching : Probability distributions, Hypothesis testing, Regression analysis, Bias–variance trade-off, Statistical thinking for machine learning, ML algorithms, Model evaluation metrics.

Mentored students and professionals transitioning into Data Science & Machine Learning, bridging statistics with modern AI workflows.
Helped learners understand when and why to apply statistical methods, not just how.

Can communicate in : English, Hindi, Kannada, Telugu.

Subjects

  • Statistics Expert

  • Machine Learning Expert

  • Data Science Intermediate-Expert

  • Mathematical Statistics Expert

  • Statistical Inference Expert

  • Time series Analysis-Demand Forecasting Expert

  • DOE (Design of experiment) Expert

  • Python 3 Expert

  • Sampling in Statistics Expert

  • R coding language Expert

  • Design of Experiment Expert

  • Probability (Discrete, Continuous, Joint Distributions, Bayes' Theorem, Random Variables) Expert

  • Statistical genetics Expert

  • Econometrics (Advanced) Expert

  • AI/ML using Python Expert

Experience

  • Associate Professor (Sep, 2016–Present) at ' 07 years experience as a teacher and tutor i teach in my own institute and other private
    Statistics Instructor / Mentor — 7 Years

    Taught Statistics and Applied Probability to engineering and data science students with a strong focus on real-world applications.

    Covered core statistical concepts including:

    Descriptive & inferential statistics

    Probability distributions

    Hypothesis testing

    Regression analysis

    Bias–variance trade-off

    Statistical thinking for machine learning

    Emphasized intuition-first teaching, connecting formulas to:

    ML algorithms

    Model evaluation metrics

    Data-driven decision making

    Designed hands-on examples using Python, NumPy, Pandas, and real datasets instead of purely theoretical problems.

    Mentored students and professionals transitioning into Data Science & Machine Learning, bridging statistics with modern AI workflows.

    Helped learners understand when and why to apply statistical methods, not just how.

Education

  • Master in Statistics (May, 2014–Sep, 2016) from Bengaluru university–scored 88

Fee details

    ₹1,000–1,500/hour (US$10.53–15.79/hour)

Courses offered

  • Statistics - Crash Course

    • ₹1000
    • Duration: 3 Months
    • Delivery mode: Online
    • Group size: 6 - 10
    • Instruction language: English, Hindi, Kannada, Telugu
    • Certificate provided: Yes
    Statistics Instructor / Mentor — 7 Years

    Taught Statistics and Applied Probability to engineering and data science students with a strong focus on real-world applications.

    Covered core statistical concepts including:

    Descriptive & inferential statistics

    Probability distributions

    Hypothesis testing

    Regression analysis

    Bias–variance trade-off
    Design of Experiment, Sampling techniques, Operation research, Statistical Inferences.
    Statistical thinking for machine learning

    Emphasized intuition-first teaching, connecting formulas to:

    ML algorithms

    Model evaluation metrics

    Data-driven decision making

    Designed hands-on examples using Python, NumPy, Pandas, and real datasets instead of purely theoretical problems.

    Mentored students and professionals transitioning into Data Science & Machine Learning, bridging statistics with modern AI workflows.

    Helped learners understand when and why to apply statistical methods, not just how.

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