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How to learn all necessary data science topics within one single course online ?



A Comprehensive Ecourse on Data Science comprising the following topics :

Statistical Techniques :

Outlier Detection:

  • Chauvenet Method

  • Dixon Thompson Method

  • Rosner's Method

  • Ten Most Recognizable Case Studies of Using Outlier Detection for Model Development

Trend Detection

  • What is a Trend and How do you detect a trend in a set of data?

  • Runs Test

Correlation Determination

  • Auto and Cross-Correlation

Risk and Uncertainty

  • What is Risk and Vulnerability?

  • Weibull’s Method

  • Numerical Analysis

  • Uncertainty Analysis

Linear Regression

Non-Linear Regression

Artificial Intelligence

Fundamentals

  • What is Artificial Neural Network(ANN)?

  • Parameter Estimation

  • Training Algorithms

  • Testing of the Network

  • Validation of the Networks

  • Example Problems

Training Algorithms

  • Quick Propagation

  • Conjugate Gradient Descent

  • Newtons Method

  • Quasi Newton

  • Levenberg Marquardt

Advanced ANN

  • Polynomial Neural Networks

  • Group Method of Data Handling

Testing ANN Performance

  • ERROR IDENTIFICATION METRICS

  • REGRESSION ERROR

  • CLASSIFICATION ERROR

  • CORRELATION IDENTIFICATION METRICS

  • EFFICIENCY IDENTIFICATION METRICS

Applications in Case Studies

  • Example Application in Water Resource Development

Software

  • No Code Software for ANN Application

Multi-criteria Decision Making Methods(MCDM)

Basics of MCDM

  • What is MCDM?

  • Working Principle of MCDM

Compensatory MCDM Methods

  • Tutorial on Analytical Hierarchy Process

  • Tutorial on Analytical Network Process

  • Tutorial on Multi-Attribute Utility Theory

  • Tutorial on EVAMIX

Outranking MCDM Methods

  • Tutorial on ELECTRE I

  • Tutorial on PROMETHEE I and II

Applications in Case Studies

  • Applications of MCDM in Water Resource Development

  • More Applications

Optimization Technique

Fundamentals

  • Fundamentals of Optimization Technique

  • Constraints

  • Classification of Optimization Techniques

Classical Optimization Techniques

  • Linear Programming

  • Dynamic Programming

  • Quadratic Programme

  • KKT Conditions

  • Dynamic Programming

  • Recursive Equation

Nature-Inspired Optimization Techniques

  • Particle Swarm Optimization

  • Ant Colony Optimization

  • Genetic Algorithm

  • Glowworm Optimization

  • FireFly Optimization

  • Mine Burst Optimization

Duration: One year and more if required

Scope of Publication: Yes

Each material will also have practice problems, real-life case study descriptions and project ideas for doing research.


You may earn also by becoming an affiliate of this course. Interested? Click here.

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