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DSTC-00447 Online (e-LMS) Graduate / Intermediate

AI for Autonomous Defense Drones and Surveillance

by - DSTC

Master AI for Autonomous Defense Drones and Surveillance in 4 weeks through hands-on, project-based online training with DSTC.

โ˜…โ˜…โ˜…โ˜…โ˜… Be the first to review โ€ข 4 Weeks ยท 40 hrs โ€ข e-Certificate Included
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From โ‚น2,500 + GST

๐Ÿ“š Syllabus & Course Curriculum

Antimicrobial Resistance (AMR)

Module-by-module breakdown of AI for Autonomous Defense Drones and Surveillance, from foundations to a certified capstone project.

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Outline

Develop a comprehensive understanding of linear algebra and calculus for AI applications โ€ข Analyze the fundamentals of probability and statistics for machine learning โ€ข Design basic neural network architectures using Python and popular deep learning libraries

Outline

Configure data pipelines for autonomous defense drones using Apache Beam and Google Cloud Dataflow โ€ข Implement data preprocessing techniques for image and sensor data using OpenCV and Pandas โ€ข Evaluate the effectiveness of feature engineering methods for improving model performance

Outline

Design and implement convolutional neural networks (CNNs) for object detection and tracking โ€ข Develop and train recurrent neural networks (RNNs) for time-series forecasting and prediction โ€ข Analyze the performance of different model architectures for autonomous defense drone applications

Outline

Implement hyperparameter tuning using grid search, random search, and Bayesian optimization โ€ข Evaluate the performance of trained models using metrics such as accuracy, precision, and recall โ€ข Develop and implement early stopping and learning rate scheduling techniques for improved training

Outline

Configure and deploy models using TensorFlow Serving and Docker containers โ€ข Implement continuous integration and continuous deployment (CI/CD) pipelines using Jenkins and GitLab โ€ข Develop and implement monitoring and logging systems for production workflows

Outline

Analyze the ethical implications of AI systems for autonomous defense drones โ€ข Develop and implement techniques for bias mitigation and fairness in AI decision-making โ€ข Evaluate the effectiveness of explainability methods for AI models

Outline

Develop business cases for the adoption of AI-powered autonomous defense drones โ€ข Implement AI solutions for real-world industry applications and case studies โ€ข Evaluate the return on investment (ROI) and cost-benefit analysis of AI-powered autonomous defense drones

Earn government-registered certification in AI for Autonomous Defense Drones and Surveillance

e-Certificate and e-Marksheet issued on successful completion.

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