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Successful completion of these courses will empower the participants with the skills mentioned against respective courses below.

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The following two courses are compulsory having outcomes listed below.

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​1. Machine Learning (ML) Engineering​

 

• Proficiency in advanced Python programming, including concurrency, parallelism, and memory management.

• Expertise in training advanced machine learning algorithms and hyperparameter tuning.

• Knowledge of distributed training techniques for machine learning models.

• Skills in deploying models using various serving frameworks and containerization/orchestration tools.

• Competence in model testing, including the use of evaluation metrics, and addressing bias and fairness.

• Experience with Python libraries for data processing, manipulation, and visualization, as well as specialized ML libraries.

• Understanding of reinforcement learning, multi-agent systems, and production-ready agent frameworks.​

 

2. Digital Engineering

 

• ​Mastery of semantic HTML5 and web components.

• Advanced skills in CSS, including layout techniques, responsive design, preprocessors, postprocessors, and CSS-in-JS.

• Proficiency in modern JavaScript (ES6+), including advanced functions, asynchronous programming, and design patterns.

• Expertise in React, with advanced state management, hooks, server-side rendering (SSR), and testing.

• Advanced knowledge of Node.js, focusing on backend development, database integration, security practices, performance optimization, DevOps, and deployment. 

 

Participants need to take two of the following three courses, outcomes being as below.

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3. Data Engineering​

 

• Advanced SQL query writing, database optimization, stored procedures, functions, replication, and clustering in MySQL.

• In-depth understanding of Amazon Simple Queue Service (SQS), including advanced concepts, integration, performance tuning, and security.

• Proficiency in designing data pipelines, including architectural patterns, data ingestion techniques, data processing frameworks, and monitoring.

• Advanced data modeling techniques, including big data modeling, performance considerations, and best practices.

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4. Cloud Engineering

 

• Advanced skills in designing workflows with AWS Step Functions, including integration with AWS services and performance optimization.

• Expertise in AWS Lambda functions, focusing on advanced usage, event-driven architectures, security, and compliance.

• Proficiency in using API Gateway, including advanced features, security, access control, monitoring, and logging.

• Advanced understanding of AWS AppSync, including GraphQL, data sources, integrations, and performance optimization.

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5. Mobile Engineering​

 

• Advanced UI design and state management in Flutter, including performance optimization, integration, plugins, testing, CI/CD, internationalization (i18n), and localization.

• Proficiency in React Native, focusing on advanced component patterns, state management, performance optimization, native modules and code, navigation, testing, CI/CD, and internationalization.

• Knowledge of cross-cutting concerns in mobile development, including security, networking, app architecture, and publishing and distribution.