Invitation to join the 12 Part E-Course on Introduction to Data Science with Real Life Examples

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You can visit the following URL to join the 12 Part E-Course on Introduction to Data Science with Real Life Examples

https://veryshorttermcourse.substack.com/s/data-science

If you have already subscribed, then Thanks for subscribing

If you want to know about the content of the course, then look below for the details :

Statistical Techniques

• Outlier Detection(Email 1)
• Chauvenet Method
• Dixon–Thompson Method
• Trend Detection(Email 2)
• What a trend is and why it matters
• How to detect a trend in a data series
• Practical examples from environmental and engineering data
• Correlation and Dependence(Email 3)
• Basics of correlation
• Auto-correlation and cross-correlation
• How correlation affects modeling and prediction
• Risk and Uncertainty(Email 4)
• What are risk and vulnerability in data-driven decisions
• Weibull’s method for modeling variability
• Uncertainty Analysis
• Regression(Email 5)
• Linear regression: fitting straight-line relationships
• Non-linear regression: handling curved relationships
• How regression feeds into prediction and decision-making

Artificial Intelligence: Artificial Neural Networks (ANN)

• Fundamentals(Email 6)
• What is an Artificial Neural Network (ANN)?
• Basic structure: inputs, hidden layers, outputs
• Parameter estimation (weights and biases)
• Model Development Workflow(Email 7)
• Training algorithms
• Testing the network on unseen data
• Validation to avoid overfitting
• Training Algorithms Covered(Email 7)
• Quick Propagation
• Conjugate Gradient Descent
• Training Algorithms Covered(Email 7)
• Newton’s Method
• Quasi-Newton
• Levenberg–Marquardt
• Advanced ANN(Email 8)
• Polynomial Neural Networks
• Group Method of Data Handling (GMDH)
• Performance Evaluation(Email 9)
• Error Identification Metrics:
• Regression error
• Classification error
• Correlation-based metrics
• Efficiency metrics

Nature-Based Optimisation Techniques

• Introduction to Optimisation (Email 10)
• Nature-Based Optimisation Techniques Part 1 (Email 11)
• Genetic Algorithm
• Water Cycle Algorithm
• Nature-Based Optimisation Techniques Part 2 (Email 12)
• Grey Wolf Optimisation
• Cuckoo Search Algorithm

Bonus

• No-code software for ANN so you can build models without heavy programming

We will send one email per week. In total, 12 emails will be sent.

Please note that the first six parts of the tutorial are FREE, and the remaining parts are PAID.

If you are interested you may click the l9oink below to join : https://veryshorttermcourse.substack.com/s/data-science