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Starts 6 June 2025 01:39

Ends 6 June 2025

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Machine Learning for a Rescue

Explore machine learning applications in software development, focusing on data-driven approaches to classify developers and predict project outcomes.
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Overview

Explore machine learning applications in software development, focusing on data-driven approaches to classify developers and predict project outcomes.

Syllabus

  • Introduction to Machine Learning
  • Overview of machine learning concepts
    Types of machine learning: supervised, unsupervised, and reinforcement learning
    The importance of data in machine learning
  • Data-Driven Software Development
  • Data collection and preprocessing methods
    Understanding datasets related to software development
    Feature selection and engineering
  • Classifying Developers
  • Techniques for developer classification
    Using demographic and behavioral data
    Case studies on developer classification
  • Predicting Project Outcomes
  • Identifying key metrics for project success
    Building predictive models for project outcomes
    Applications of predictive analytics in project management
  • Machine Learning Algorithms
  • Overview of classification algorithms: decision trees, random forests, support vector machines
    Regression models for prediction
    Clustering techniques and their application
  • Implementing Machine Learning Models
  • Model training and evaluation
    Cross-validation and hyperparameter tuning
    Deployment of machine learning models in software environments
  • Tools and Platforms
  • Introduction to popular machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)
    Using cloud-based platforms for machine learning (e.g., AWS, Google Cloud AI)
    Tool integration in software development pipelines
  • Ethical Considerations and Best Practices
  • Understanding biases in algorithms
    Ensuring fairness and transparency in model predictions
    Responsible use of machine learning in development contexts
  • Future Trends and Applications
  • Emerging technologies in machine learning for software development
    The role of AI in collaborative development environments
    Future challenges and opportunities
  • Capstone Project
  • Define a project scope involving real-world data
    Develop a classification or prediction model
    Present findings and reflect on the project outcomes

Subjects

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