• Fundamentals
  • Performance Engineering
  • Capacity Management
  • Data Mining and Machine Learning
  • Fundamentals

    Statistics
    Topics covered include ways to explain the purpose of measures of location, variability, skewness, mean, median, percentile, quantiles and calculate probabilities, identify, calculate and interpret confidence intervals for means and proportions, conduct and interpret hypothesis tests using Student's t-test, compute and use regression equations for data to make predictions, regression analysis, residual analysis, correlation, etc.

    Programming in R
    Topics include - Data types, subsetting Reading/writing data, control structures, functions, simulation, plotting and visualizing.

  • Performance Engineering

    Topics include - Lifecyle of performance engineering, testing, management & monitoring, diagnostics and tuning. Modelling techniques i.e. statistical, simulation and analytical.

    Operational and queueing theory, applications of Little's Law, workload characterization, general queuing networks, simulations (discrete event, monte carlo, etc), time series and regression modelling.
    Tools of trade will also be covered - JMeter, HP Loadrunner, Rational Performance Tester, etc.

  • Capacity Management

    Topic covered include - Requirements gathering for capacity management, non-functional requirements gathering, workload characterization and modelling (both simulated and statistical),

    time series analysis and forecasting (ARIMA, Holt Winters, etc). Linear, logarithmic and exponential modelling.

  • Data Mining and Machine Learning

    An introduction to machine learning and statistical pattern recognition. Topics include: Supervised learning (eg. generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines),

    Unsupervised learning (eg. clustering, dimensionality reduction, kernel methods), reinforcement learning and adaptive control.

Client Logo
Client Logo
Client Logo
Client Logo
Client Logo
Client Logo