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Data Science With Python
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Data Science With Python

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The goal of data science is to construct the means for extracting business-focused insights from data. This requires an understanding of how value and information flows in a business, and the ability to use that understanding to identify business opportunities.

Introduction to data science

  • What is Data Science and why is it so important ?
  • Overview of Data Science and Analytics
  • Mathematics for Data Science
  1. Probability and Inferential Statistics
  2. Linear Algebra 
  3. Calculus
  • Introduction to Python
  1. Basic Python Programming Constructs
  2. Functions in Python, NumPy Basics
  3. Learn Pandas basic concepts, work with series
  4. Work with Pandas Data Frame (Advanced)

Data Visualization Techniques

  • Understanding and Visualizing Data
  1. Learn to utlize your own decision-making framework to achieve desired outcomes.
  2. Evaluate decisions by looking at key performance measures and and determining their implications for stackholders.
  • Data Visualization in Python using Matplot.

Decision Making and predictive analysis

  • Modeling uncertainty and Risk
  1. Use estimates of probable future outcomes for simple Yes/No decisions, based on increasignly complex modeling situations.
  2. Develop and use Monte Carlo simulation to examine outcomes that very based on mutiple, interdependent decisions.
  • Optimization and Modeling Simultaneous Decisions
  1. Create an optimization model for linear and non-linear decision situations.
  2. Use data models to predict and optimize outcomes in complex situations invloving multiple, simulataneous decisions.

Machine Learning (Supervised Learning) Part - I

  • Linear Regression
  • Logistic regression
  • Generalization & Non Linearity
  • Recursive Partitioning(Decision Trees)
  • Ensemble Models(Random Forest, Bagging & Boosting(ada, gbm etc))
  • Support Vector Machines(SVM)
  • K-Nearest neighbours
  • Naive Bayes
  • usage

Machine Learning (Unsupervised Learning) Part - II

  • Clustering
  1. K-means clustering
  2. K nearest neighbours
  3. Association rule learning
  • Reinforcement Learning
  1. Markov Decision
  2. Monte Carlo Prediction

 

 

Two certifications will be provided to participants:

  1. Microsoft Certified Technology Associate Certification certified by Microsoft.
  2. Institution Certification certified by DOIS Education & Technologies Private Limited

 

Duration of Course: 3 Months

Course Price : 35,000 INR + GST OR 610 USD