DATA SCIENCE

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining

Course Duration:

4 Months

 

Targeted Audience:

Software Engineers, Web Developers, Engineering Graduates and Graduates from Computer Science/IT

Course Pre-Requisites:

Any programming knowledge


Course Curriculum

INTRODUCTION TO PYTHON

  • Why python, different tools used for python and setup
  • Data structures
  • Conditional statements, looping concepts and other functionalities

  • What is data science, machine learning and Artificial Intelligence
  • Why is it interesting
  • Real time use cases and where all we are using

  • Descriptive statistics, distributions, hypothesis testing
  • Conditional probability, priors, posteriors, and maximum likelihood

  • Types of data
  • Computing simple statistics
    • Means, modes, median, variances, standard deviations, MAE, RMSE.
  • Simple visualizations
    • Histograms
    • Boxplots
    • Scatterplots
    • Time series

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Steps for machine learning algorithm
    • Data preprocessing

  • Models, Implementation, Analysis
  • Grid search, Cross validation
  • Measuring performance of a model
    • Accuracy, ROC curves, precision-recall curves, Regularization.

  • Dimensionality reduction techniques
    • Feature selection
    • Feature extraction

  • Real time project in data science.

  • Introduction
  • Hands-on by participants
  • Discussion of results

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