Complete Pragmatic AI Labs Learning Path 2024: From Python to Rust to Cloud to MLOps (75 Course Guide)

Welcome to the comprehensive 2024 learning path from Pragmatic AI Labs. This curated collection of 75 LinkedIn Learning courses is designed to take you from foundational programming to advanced cloud architecture and MLOps. Whether you're starting your journey in tech or looking to upgrade your skills, this path provides a structured approach to mastering modern development practices.

🚀 Foundation Track

Python and Rust Fundamentals

• Complete Guide to Python Fundamentals for MLOps
• Rust Programming: From Fundamentals to Advanced Concepts
• Using Rust with Python
• Rust for Data Engineering
• Rust AWS Lambda

🤖 AI and Machine Learning Track

Large Language Models and GenAI

• Introduction to LLM Vulnerabilities
• Responsible Generative AI and Local LLMs
• Generative AI and Large Language Models on AWS
• Small Language Models and Llamafile
• Rust LLMOps

MLOps and Tools

• MLOps Tools: MLflow and Hugging Face
• Best Practices for Integrating GitHub Models
• Essentials of MLOps with Azure 1: Introduction
• Essentials of MLOps with Azure 2: Databricks MLflow and MLflow Tracking
• Essentials of MLOps with Azure 3: Spark MLflow Projects on Databricks
• Essentials of MLOps with Azure 4: Spark MLflow Models and Model Registry

☁️ Cloud Certifications Track

AWS Certifications

Machine Learning Specialty

• AWS Certified Machine Learning Specialty: Data Engineering
• AWS Certified Machine Learning Specialty: Exploratory Data Analysis
• AWS Certified Machine Learning Specialty: Modeling
• AWS Certified Machine Learning Specialty: Implementation and Operations

Security Specialty

• AWS Security Specialty: Threat Detection and Incident Response
• AWS Security Specialty: Security Logging and Monitoring
• AWS Security Specialty: Infrastructure Security
• AWS Security Specialty: Identity and Access Management
• AWS Security Specialty: Data Protection
• AWS Security Specialty: Management and Security Governance

Advanced Networking Specialty

• AWS Advanced Networking: Network Design
• AWS Advanced Networking: Network Implementation
• AWS Advanced Networking: Network Management and Operation
• AWS Advanced Networking: Security Compliance and Governance

Solutions Architect Professional

• AWS Solutions Architect Professional: Design Solutions
• AWS Solutions Architect Professional: New Solutions
• AWS Solutions Architect Professional: Continuous Improvement
• AWS Solutions Architect Professional: Workload Migration

Azure Certifications

Data Engineer Associate (DP-203)

• Azure Data Engineer: Monitor and Optimize
• Azure Data Engineer: Data Security

Data Scientist Associate (DP-100)

• Azure Data Scientist: Manage Azure Resources
• Azure Data Scientist: Run Experiments and Train Models
• Azure Data Scientist: Deploy and Operationalize
• Azure Data Scientist: Implement Responsible ML

Google Cloud Certifications

Professional Data Engineer

• GCP Data Engineer: Designing Data Processing Systems
• GCP Data Engineer: Building and Operationalizing
• GCP Data Engineer: Operationalizing ML Models
• GCP Data Engineer: Solution Quality

Professional Machine Learning Engineer

• GCP ML Engineer: Framing ML Problems
• GCP ML Engineer: Architecting ML Solution
• GCP ML Engineer: Developing ML Models
• GCP ML Engineer: Automating ML Pipelines

Professional Cloud Architect

• GCP Cloud Architect: Design and Planning
• GCP Cloud Architect: Managing Infrastructure
• GCP Cloud Architect: Security and Compliance
• GCP Cloud Architect: Managing Implementation
• GCP Cloud Architect: Solution Reliability

📊 Data Engineering Track

Databricks Certification Path

• Databricks: Lakehouse Platform
• Databricks: ELT with Spark SQL and Python
• Databricks: Incremental Data Processing
• Databricks: Production Pipelines
• Databricks: Data Governance
• Databricks: Data Access with Unity Catalog

Data Platforms and Tools

• Data Platforms: Spark to Snowflake
• MySQL for Data Engineering
• Vector Graph and DynamoDB

🔐 GitHub and Security Track

GitHub Administration

• GitHub Foundations: Privacy, Security, and Administration
• GitHub Admin: Support Users and Stakeholders
• GitHub Admin: User Identities and Authentication
• GitHub Admin: Deployment and Licensing
• GitHub Admin: Access and Permissions
• GitHub Admin: Secure Software Development
• GitHub Admin: Manage Actions
• GitHub Admin: Manage Packages

🔄 Agile Practices

• Agile Practices Using AI

This comprehensive learning path is designed to be completed over the course of 2024, with each track building upon the previous ones. The courses are structured to provide both breadth and depth in modern software development, cloud architecture, and AI/ML operations. Whether you're aiming for certification or practical knowledge, this path provides the resources you need to succeed in today's tech landscape.

Recommended Courses

Based on this article's content, here are some courses that might interest you:

1. AWS Advanced AI Engineering (1 week)
   Production LLM architecture patterns using Rust, AWS, and Bedrock.

2. Enterprise AI Operations with AWS (2 weeks)
   Master enterprise AI operations with AWS services

3. Python Essentials for MLOps (5 weeks)
   Learn essential Python programming skills required for modern Machine Learning Operations (MLOps). Master fundamentals through advanced concepts with hands-on practice in data science libraries and ML application development.

4. Natural Language AI with Bedrock (1 week)
   Get started with Natural Language Processing using Amazon Bedrock in this introductory course focused on building basic NLP applications. Learn the fundamentals of text processing pipelines and how to leverage Bedrock's core features while following AWS best practices.

5. Natural Language Processing with Amazon Bedrock (2 weeks)
   Build production NLP systems with Amazon Bedrock

Learn more at Pragmatic AI Labs