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          AI-ML-hero

          AI & Machine Learning

          Build AI and machine learning skills, one course at a time.

          Build practical skills to design, deploy, and maintain the AI systems that drive modern business transformation. Take individual courses or combine them to master the tools and methodologies that power production-grade AI applications.    

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          Get started on your AI and machine learning journey. Tell us a little about you and we'll get in touch with more info.

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          AI-ML-courses

          4 courses to build real AI and machine learning skills

          Master the complete AI development lifecycle through four specialized courses. Take any course individually or combine them all to complete the pathway. From applied machine learning and data infrastructure to production operations and system reliability, you'll learn to build, deploy, and maintain intelligent systems that scale in real-world environments.

          Applied AI & Deep Learning in Action

          • What you'll build: Deep learning models, NLP sentiment analyzer, computer vision classifier, LangChain-powered chatbot
          • Key technologies: PyTorch, Hugging Face, TensorFlow, LangChain, Vector databases, BERT, CNNs
          • Skills you'll gain: Neural network design, transformer architectures, responsible AI deployment, model evaluation

          Data Engineering & Automation with AI

          • What you'll build: Automated data pipelines, real-time streaming workflows, RAG-powered knowledge base, MLflow tracking system
          • Key technologies: Apache Airflow, Kafka, dbt, Spark, Docker, Terraform, Vector databases
          • Skills you'll gain: Pipeline orchestration, feature engineering, data governance, infrastructure automation

          MLOps & AI Infrastructure

          • What you'll build: End-to-end ML pipeline, model deployment system, governance framework, strategic infrastructure roadmap
          • Key technologies: Docker, GCP Cloud Composer, CI/CD pipelines, Model registries, Kubernetes
          • Skills you'll gain: Production ML workflows, model lifecycle management, AI governance, scalable architecture design

          AI Systems Engineering & Reliability

          • What you'll build: Production monitoring dashboard, automated testing suite, fault-tolerant AI system, reliability framework
          • Key technologies: Prometheus, Grafana, Kubernetes, AWS/GCP/Azure, CI/CD, Chaos engineering
          • Skills you'll gain: System observability, reliability engineering, incident response, performance optimization

          OUR LEARNERS WORK AT TOP COMPANIES ACROSS THE GLOBE

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          Course Highlights

          Master the complete journey from machine learning fundamentals to production AI systems. Learn to build neural networks with PyTorch, work with transformers and NLP pipelines, and deploy responsible AI solutions using LangChain and vector databases. This hands-on course gives you immediately applicable skills whether you're transitioning into AI development or enhancing existing technical expertise.

          Explore course

          Transform raw data into AI-ready pipelines that scale. Master cloud architectures, streaming workflows with Kafka, and automated orchestration using Airflow while connecting enterprise data to generative AI systems. Perfect for professionals ready to build the robust data foundations that modern AI applications depend on.

          Explore course

          Move beyond model building to strategic AI infrastructure leadership. Learn to architect end-to-end ML pipelines, implement governance frameworks, and create scalable deployment strategies while balancing technical excellence with business outcomes. Gain the strategic expertise needed to lead AI transformation initiatives.

          Explore course

          Master the operational skills that separate experimental AI from production-grade systems. Learn to monitor AI performance, implement automated recovery, diagnose system failures, and optimize infrastructure costs while maintaining reliability at scale. Get the skills that make you invaluable as AI becomes mission-critical to business operations.

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          Why this learning pathway works

          Learn at your own pace, with built-in flexibility 
          Each course is offered independently, so you can start with a single topic or progress through all four courses in this discipline over time. Take courses in the order that fits your interests, background, and schedule, or complete a full pathway to build a cohesive understanding of how AI systems are developed and maintained.

          Curriculum designed for today’s AI systems landscape
          This pathway reflects how modern organizations build and operate AI systems in real-world environments. You’ll work across applied machine learning, data engineering, MLOps, and systems reliability, using current tools, platforms, and workflows that support scalable, production-grade AI development.
           
          Applied learning through hands-on practice 
          Each course balances instruction with active learning. You’ll spend a significant portion of time working through practical exercises and projects that reinforce core machine learning concepts, data pipelines, deployment workflows, and operational practices. This hands-on structure supports deeper engagement with the tools and processes used to build, deploy, and maintain AI systems.

           

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          Tuition for each course is $2,950

          Take two courses and qualify for the additional two courses for free. With this bundle discount, all four courses in this pathway are available for a total tuition of $5,900.*

          *Eligibility is based on terms and conditions.

          When you enroll in two eligible courses within this learning pathway, you become eligible for a bundle discount that allows you to take the remaining two courses in the pathway at no additional tuition or fee cost.

          The bundle discount applies only after enrollment in two qualifying courses. Students must enroll in the four courses individually and are charged applicable tuition and fees after enrollment occurs.

          Bundle eligibility, course availability, and timing are subject to terms and conditions.

          Divide the tuition for an individual course into two, three, or four payments while enrolled.

          As low as $712.50 per course.

          Apply for a 0% interest loan from Climb Credit

          This option allows students to pay the tuition of an enrolled course over 9 months per course.

          Students enrolling in multiple eligible courses may qualify for extended payment terms under the bundle loan option.

          Loan approval subject to eligibility.

          Apply for a loan from Climb Credit.

          Choose immediate repayment or an interest-only option.

          Interest rates range from 6.5–15%, with loan terms from 2–5 years (6.99–17.99% APR).

          Loan approval subject to eligibility. Loan terms displayed are effective as of 1/1/2026.

          Show off your new skills

          You get a digital badge for every individual course you complete. Complete all courses in the discipline, get your pathway badge, and add it to your LinkedIn profile to showcase your new skills to your network.  
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          KEY TAKEAWAYS  

          Completing all of the courses in AI & Machine Learning will equip you with these essential AI engineering skills:

          BUILD PRODUCTION-READY AI SYSTEMS FROM CONCEPT TO DEPLOYMENT

          You'll master the complete AI development lifecycle, from training deep learning models with PyTorch and transformers to building scalable data pipelines with Airflow and Kafka. You'll learn to integrate AI capabilities into real applications, deploy models using containerization and cloud infrastructure, and create end-to-end solutions that solve genuine business problems.

          ARCHITECT SCALABLE AI INFRASTRUCTURE AND DATA OPERATIONS

          You'll design robust data engineering workflows that support AI at scale, implementing automated pipelines for data ingestion, transformation, and feature management while connecting enterprise systems to generative AI through vector databases and RAG architectures. You'll master MLOps practices for model lifecycle management, governance frameworks, and infrastructure-as-code deployments.

          ENSURE AI RELIABILITY AND OPERATIONAL EXCELLENCE

          You'll develop the expertise to monitor, troubleshoot, and optimize AI systems in production environments, implementing observability solutions, automated testing, and incident response procedures. You'll learn to balance performance with cost-efficiency, maintain system reliability under pressure, and apply DevOps principles specifically tailored for AI workloads—culminating in portfolio-ready projects that demonstrate your ability to build, deploy, and operate intelligent systems at enterprise scale.

          INSTRUCTORS WITH REAL-WORLD CRED

          Learn from AI & machine learning pros who bring hands-on experience straight from the field to the classroom. Every GA instructor is committed to giving the personalized feedback and support you need to crush your goals every step of the way.
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          Learning AI skills is no longer optional. Tell us a little about you—and we’ll get in touch with more info.

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          QUESTIONS? WE'VE GOT ANSWERS.

          AI is reshaping every role and every industry, and learning AI skills to enhance your role is no longer optional. General Assembly's courses in AI and machine learning provide live, cohort-based training that equips learners with the in-demand machine learning and AI skills to design, deploy, and maintain the AI systems that drive modern business transformation.
          Absolutely. Our flexible pathway approach lets you build your learning schedule to fit your life. Take multiple courses simultaneously, take one course at a time, or create your own custom learning timeline.
          Yes. You can bundle any four courses together to “build your own” learning pathway, or simply take as many courses from as many disciplines as you’d like. When it comes to learning at GA, the choice is yours. 

          Yes. When you pass a course, you’ll receive a LinkedIn-verified digital badge, and if you complete four courses in a pathway, you’ll also receive a pathway badge. Thousands of GA alumni around the world use these badges to demonstrate their skills to their LinkedIn networks, potential employers, and more. Our courses are well-regarded by many top employers, who contribute to our curriculum and partner with us to train their own teams.

          Some courses are truly beginner-friendly. Others require certain experience and knowledge. 

          Admissions requirements and recommended experience are explained in additional detail on each course webpage, as well as in the Student Catalog. Our Admissions team can discuss your background and learning goals to advise if the course (our courses) you’re interested in is a good fit for you.

          Yes. All of our courses are designed for busy professionals with full-time work commitments. There’s no prework and the workload is designed to be manageable with a full-time job. If you need to miss a session or two, we offer resources to help you catch up. We recommend you discuss any planned absences with your instructor.

          Our Admissions team is here to help and can advise whether this pathway is right for you and your learning goals. You can also:

          • Attend an info session online
          • Explore your financing options
          • Apply to enroll in the course.*

          *Course modality options vary by location, pending market availability. Please contact our Admissions team to discuss what version is available in your location.

          Education does not guarantee outcomes, including, but not limited to, employment or future earnings potential.
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