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Introduction to Data Science:

  • What is DS?
  • Why is it needed? , Worth the hype?
  • What are major fields under DS?
  • A few industry application examples, Future Demand & requirement of DS, Different categories of job options in DS.

An overview of different stages under Data Analysis

  • Data Summarization/Descriptive Analytics, Data Interpretation, Extraction of Pattern
  • Data Preprocessing: Why? How? What?
  • Data Modeling
  • Cross Validation, Improve performance accuracy

Machine Learning

  • Introduction to Machine Learning:
  • Few examples of Practical Applications,Future Demand & requirement of ML
  • Supervised Learning
  • Decision Trees
  • Random Forest
  • Navie Bayes, Bayesian networks, Generative vs Discriminative
  • KNN algorithm
  • Support Vector Machine
  • Ensemble Modeling
  • Morkov Models
  • Unsupervised Learning
  • Arules, FP Trees
  • Recommendation Systems: Collaborative Filtering, SVD
  • Clustering Techniques:
  • K-means, k-medoids,
  • EM clustering etc
  • PCA, Error Metrics: Confusion Matrix, Cross Validation etc
  • Curse of Dimensionality, Bias vs Variance, Improving Accuracy
  • Practical real world examples and solving problems
  • Introduction to R programming and working on project(will provide solution and explain)


  • Linear Regression: Assumptions, Gradient Descent, model analysis, tweaking parameters. Logistic Regression
  • Hypothesis Testing: Null, Alternate Hypothesis, Normal distribution, Type 1,2 errors
  • Sampling Techniques: Random, System, Stratified, Quota etc
  • Distributions: Poisson, Bernoulli, Binomial, Exponential, Normal etc
  • ANOVA, Chisquare, t-test etc.

Very well organized and conceived. By following the course, I was able to learn and build on the concepts with minimal questions or frustration. It taught me what I was looking to learn, was well organized, and well-paced. I’m already applying what I learned at work.


The practical exercises were useful in offering ‘hands on’ experience. The interactive atmosphere and live examples used for illustration were refreshing.


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  • 55 Days


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