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Mar 24, 2024
17 min read

AI Curriculum Study Plan (Curriculum - AI)

AI Study Plan for Developers, Architects, Business Analysts, and Scrum Masters

Here’s a structured AI Curriculum Study Plan tailored for developers, architects, business analysts, requirement engineers, product owners, and scrum masters, organized by skill level and roles. Resources are sourced from platforms like Microsoft Learn, Coursera, Pluralsight, and DeepLearning.AI, with direct links to courses.

Foundational AI Concepts (Beginner)

Target Audience: All roles.

  1. Introduction to AI:

  2. AI Ethics and Governance:

Intermediate AI Topics

Developers & Architects

  1. Machine Learning Engineering:

  2. AI Architecture:

Business Analysts & Product Owners

  1. AI Strategy for Business:

  2. Requirements Engineering for AI:

Scrum Masters

  1. Agile AI Projects:

Advanced AI Topics

  1. Deep Learning:

  2. AI Deployment & MLOps:

  3. Generative AI & Copilots:

Role-Specialized Topics

Product Owners & Business Analysts

  1. AI-Driven Product Management:

Architects

  1. Scalable AI Systems:

Scrum Masters

  1. AI Project Governance:

Specialized Topics

  1. Microsoft 365 Copilot:

  2. Generative AI:

  3. AI in Cybersecurity:

Certifications

  1. Microsoft:
  2. DeepLearning.AI:

Learning Tips

  • Start with beginner courses to build foundational knowledge.
  • Use role-specific intermediate courses to align with your job function.
  • Advanced/specialized courses require hands-on practice (e.g., Azure Labs, Kaggle).
  • Pair certifications with real-world projects for career advancement.

(Due to technical issues, the search service is temporarily unavailable.)

Here’s an expanded AI Curriculum Study Plan with direct links to individual courses, modules, and tutorials (no collections), organized by role and skill level:

Foundational AI Concepts (Beginner)

Target Audience: All roles.

  1. Introduction to AI:

  2. AI Ethics:

Intermediate AI Topics

Developers & Architects

  1. Machine Learning:

  2. AI Engineering:

Business Analysts & Product Owners

  1. AI Strategy:

  2. Requirements Engineering:

Scrum Masters

  1. Agile AI Projects:

Advanced AI Topics

  1. Deep Learning:

  2. MLOps & Deployment:

  3. Generative AI:

Role-Specific Specializations

Product Owners & Analysts

  1. AI Product Management:

Architects

  1. AI Systems Design:

Scrum Masters

  1. AI Project Governance:

Specialized Topics

  1. Microsoft 365 Copilot:

  2. Generative AI Tools:

  3. AI Security:

Certification Prep

Hands-On Practice

Learning Path Recommendations

  1. Beginners: Start with AI For Everyone and Microsoft AI Fundamentals.
  2. Developers: Focus on Python, supervised learning, and Azure AI modules.
  3. Product Owners: Prioritize AI strategy, use case identification, and product management courses.
  4. Architects: Dive into system design, MLOps, and scalability.

Let me know if you need more granularity for a specific role! 🔍

(Due to technical issues, the search service is temporarily unavailable.)

Here’s an expanded plan with additional individual courses from Pluralsight and Coursera, organized by role and skill level:

Foundational AI Concepts (Beginner)

For All Roles:

  1. Pluralsight:

  2. Coursera:

Intermediate AI Topics

Developers & Architects

  1. Pluralsight:

  2. Coursera:

Business Analysts & Product Owners

  1. Pluralsight:

  2. Coursera:

Scrum Masters & Requirement Engineers

  1. Pluralsight:

  2. Coursera:

Advanced AI Topics

  1. Pluralsight:

  2. Coursera:

Role-Specific Specializations

Architects

  1. Pluralsight:

  2. Coursera:

Product Owners & Analysts

  1. Coursera:

Developers

  1. Pluralsight:

Specialized Topics

Microsoft 365 Copilot

  1. Pluralsight:

  2. Coursera:

Generative AI

  1. Pluralsight:

  2. Coursera:

Hands-On Labs & Projects

  1. Pluralsight:

  2. Coursera:

Certifications

  1. Coursera:

  2. Pluralsight:

Learning Tips

  • Developers: Pair Pluralsight’s hands-on labs with Coursera’s structured specializations (e.g., TensorFlow).
  • Architects: Focus on Pluralsight’s system design courses and Coursera’s MLOps.
  • Business Roles: Prioritize strategy and ethics courses from Coursera and Pluralsight.

Let me know if you need further refinements! 🚀

(Due to technical issues, the search service is temporarily unavailable.)

Here’s an expanded list of individual courses and tutorials tailored specifically for developers and architects, with additional resources from Pluralsight, Coursera, and Microsoft Learn:

Core AI/ML Development (Developers)

Machine Learning & Engineering

  1. Pluralsight:

  2. Coursera:

  3. Microsoft Learn:

Advanced AI Development

Deep Learning & NLP

  1. Pluralsight:

  2. Coursera:

  3. Microsoft Learn:

AI Architecture & System Design

Cloud AI Solutions (Architects)

  1. Pluralsight:

  2. Coursera:

  3. Microsoft Learn:

Tools & Frameworks

For Developers

  1. Pluralsight:

  2. Coursera:

Specialized Areas

MLOps & Deployment

  1. Pluralsight:

  2. Coursera:

Certifications

  1. Pluralsight:

  2. Coursera:

Hands-On Practice

  1. Pluralsight Labs:

  2. Coursera Projects:

Specialized Topics for Architects

  1. Scalability & Security:

  2. Generative AI Architecture:

Learning Path Recommendations

  • Developers: Focus on Python, TensorFlow/PyTorch, and MLOps.
  • Architects: Prioritize cloud AI design, scalability, and security.
  • Both: Pair certifications (e.g., AWS/Azure) with hands-on labs for job readiness.

Let me know if you need further refinements! 🚀

(Due to technical issues, the search service is temporarily unavailable.)

Here’s an expanded Java and Python-specific AI/ML curriculum for developers and architects, with direct links to courses, tutorials, and certifications:

Python-Focused AI/ML

Foundational Python for AI

  1. Coursera:

  2. Pluralsight:

Intermediate Python AI Development

  1. Machine Learning with Python:

  2. Deep Learning:

Advanced Python AI/ML

  1. MLOps & Deployment:

  2. Generative AI with Python:

Java-Focused AI/ML

Foundational Java for AI

  1. Coursera:

  2. Pluralsight:

Intermediate Java AI Development

  1. Machine Learning with Java:

  2. Deep Learning in Java:

Advanced Java AI/ML

  1. Enterprise AI with Java:

  2. Java-Based NLP:

Frameworks & Libraries

Python

  1. TensorFlow/PyTorch:

  2. Scikit-Learn:

Java

  1. Deeplearning4j & Weka:

  2. Apache OpenNLP:

Certifications

Python

  1. Coursera:

  2. Microsoft Learn:

Java

  1. Oracle:
  2. Pluralsight:

Hands-On Projects

Python

  1. Coursera:

  2. Pluralsight:

Java

  1. Pluralsight:

Specialized Topics

Python

Java

Learning Tips

  • Python Developers: Prioritize TensorFlow/PyTorch, scikit-learn, and Generative AI frameworks.
  • Java Developers: Focus on Deeplearning4j, Apache Spark MLlib, and enterprise integration patterns.
  • Architects: Combine Python/Java courses with cloud AI design (e.g., AWS SageMaker, Azure ML).

Let me know if you need further refinements! 🚀

(Due to technical issues, the search service is temporarily unavailable.)

Here’s a structured AI curriculum organized by roles and skill levels (Beginner, Intermediate, Advanced, Specialized), with direct links to individual courses and tutorials:

1. Developers

1.1 Beginner

1.2 Intermediate

1.3 Advanced

1.4 Specialized Topics

2. Architects

2.1 Beginner

2.2 Intermediate

2.3 Advanced

2.4 Specialized Topics

3. Business Analysts

3.1 Beginner

3.2 Intermediate

3.3 Advanced

3.4 Specialized Topics

4. Requirement Engineers

4.1 Beginner

4.2 Intermediate

4.3 Advanced

5. Product Owners

5.1 Beginner

5.2 Intermediate

5.3 Advanced

5.4 Specialized Topics

6. Scrum Masters

6.1 Beginner

6.2 Intermediate

6.3 Advanced

Specialized Topics Across Roles

  1. Microsoft 365 Copilot:
  2. AI Ethics:
  3. Generative AI:

Learning Pathways

  • Beginners: Start with foundational AI and role-specific basics.
  • Intermediate: Dive into frameworks, strategy, or governance.
  • Advanced: Focus on scalability, MLOps, or specialized tools (e.g., Copilot).

Let me know if you need further customization! 🚀

(Due to technical issues, the search service is temporarily unavailable.)

Here’s an updated curriculum with Java-specific and technology-agnostic AI courses (e.g., prompt engineering, agentic AI, LangChain4J, Spring AI) integrated into each role and skill level:

1. Developers

1.1 Beginner

1.2 Intermediate

1.3 Advanced

1.4 Specialized Topics

2. Architects

2.1 Beginner

2.2 Intermediate

2.3 Advanced

2.4 Specialized Topics

3. Business Analysts

3.1 Beginner

3.2 Intermediate

3.3 Advanced

4. Requirement Engineers

4.1 Beginner

4.2 Intermediate

5. Product Owners

5.1 Beginner

5.2 Intermediate

6. Scrum Masters

6.1 Beginner

6.2 Intermediate

Cross-Role Specialized Topics

Java AI Frameworks

  1. Spring AI:

  2. LangChain4J:

Agentic AI

Prompt Engineering

Application Frameworks

Hands-On Labs

Certifications

Key Learning Paths

  • Java Developers:
    • Start with Java Fundamentals for AI → Spring AI → LangChain4J.
  • Architects:
    • AI System Design → Multi-Agent Systems → Distributed AI with Kafka.
  • Tech-Agnostic Roles:
    • Prompt Engineering → Agentic AI → LangChain/LangChain4J.

Let me know if you need more details! 🚀

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