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Cloud AI and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing industries by enabling businesses to automate processes, gain insights from data, and create intelligent systems. Our expert-led AI/ML courses focus on teaching you how to design, implement, and manage AI and ML solutions using leading cloud platforms such as Microsoft Azure, AWS, and Google Cloud. From foundational concepts to advanced model development, our courses equip professionals with the skills to work with data, build models, and deploy AI-driven solutions across cloud environments. Whether you’re new to AI or looking to master machine learning at scale, our comprehensive training provides hands-on experience and industry-recognized knowledge.

AI/ML Fundamentals

Our AI/ML Fundamentals course provides an introduction to AI and machine learning, covering the core concepts of supervised and unsupervised learning, model training, and deployment in cloud environments. This one-day course is ideal for professionals seeking foundational knowledge without diving into advanced algorithms.

Key Topics

  • AI/ML Fundamentals
  • Introduction to Supervised and Unsupervised Learning
  • Cloud Platforms for AI/ML (Azure, AWS, GCP)
  • Basic Model Training and Evaluation
  • Data Preparation and Feature Engineering
  • AI/ML Tools and Frameworks (TensorFlow, PyTorch, etc.)

Duration: 1 Day

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AI & ML Essentials

This course dives deeper into AI and ML concepts, focusing on real-world applications such as image recognition, natural language processing, and predictive analytics. Participants will learn to design, train, and deploy AI/ML models using cloud-native tools and services from Azure, AWS, and Google Cloud.

Benefits

  • Gain hands-on experience with popular AI/ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
  • Learn to build and deploy machine learning models using Azure ML, AWS SageMaker, and Google Cloud AI Platform.
  • Master techniques for data preparation, feature engineering, and model tuning.
  • Understand the AI/ML lifecycle, from model development to deployment in production environments.
  • Prepare for AI/ML certifications from Microsoft, AWS, and Google.

What to expect

  • Work with cloud-native AI/ML tools like Azure Machine Learning, Azure AI Studio, AWS SageMaker, and Google AI Platform.
  • Design, train, and optimize models for tasks such as image recognition, NLP, and predictive analytics.
  • Understand model lifecycle management, including versioning, deployment, and monitoring.
  • Learn AI/ML best practices and industry use cases.

Interested?

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Audience

This course is ideal for:
  • Data scientists, developers, and IT professionals looking to expand their skills in AI/ML.
  • Cloud engineers and architects responsible for deploying AI solutions.
  • AI/ML practitioners seeking hands-on experience in model building and deployment.
  • Professionals managing hybrid or multi-cloud environments with AI/ML workloads.

Duration

2 Days

Delivery Mode

• Online • In-person

Key topics include

  • AI/ML Fundamentals
  • Data Wrangling and Feature Engineering
  • Supervised, Unsupervised, and Reinforcement Learning
  • Building, Training, and Evaluating Models
  • AI/ML in Production: Model Deployment and Monitoring
  • AI and Machine Learning in Hybrid and Multi-cloud Environments
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GCP AI & ML Essentials

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AWS AI & ML Essentials

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Azure AI & ML Essentials

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TensorFlow & PyTorch for AI

Deep learning frameworks like TensorFlow and PyTorch are essential for building advanced AI models. This course focuses on developing neural networks and deep learning applications using these powerful libraries, providing hands-on experience with real-world datasets.

Benefits

  • Learn to develop neural networks, CNNs, and RNNs using TensorFlow and PyTorch.
  • Gain practical experience with deep learning techniques such as transfer learning and hyperparameter tuning.
  • Understand how to scale AI workloads using cloud infrastructure.

Key topics include

  • Introduction to Deep Learning with TensorFlow and PyTorch
  • Neural Networks: CNNs, RNNs, and Transformers
  • Model Training, Tuning, and Optimization
  • Transfer Learning and Pre-trained Models
  • Cloud-based Deep Learning with Azure, AWS, and Google Cloud

Delivery Mode:

• Online • In-person

Duration:

2 Days

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AI/ML in Production

Building AI models is only the first step—deploying them effectively in production is crucial. This course focuses on the full lifecycle of AI/ML models, including deployment, monitoring, and model retraining in cloud environments.

Benefits

  • Understand how to deploy AI/ML models in production environments using Azure, AWS, and Google Cloud.
  • Learn how to monitor model performance and implement model versioning.
  • Develop strategies for model retraining, drift detection, and continuous improvement.

Key topics include

  • AI/ML Model Deployment in Cloud Environments
  • Monitoring and Managing Model Performance
  • Implementing Model Versioning and Rollbacks
  • Model Retraining and Drift Detection

Delivery Mode:

• Online • In-person

Duration:

2 Days

Interested?

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AI & Machine Learning Bootcamp

Our intensive AI & Machine Learning Bootcamp is designed for professionals seeking advanced hands-on experience in building, training, and deploying AI/ML models. This program covers topics such as deep learning, model optimization, cloud scaling, and automation. Participants will engage in real-world scenarios and labs to prepare for AI/ML production workloads in Azure, AWS, or Google Cloud.

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Certifications

AI/ML certifications are becoming essential for professionals responsible for designing and deploying intelligent systems. We offer comprehensive training to help you prepare for certifications

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Frequently asked Questions

We offer specialized AI/ML training for Microsoft Azure, AWS, and Google Cloud. Each course is tailored to the platform’s unique AI/ML services such as Azure Machine Learning, AWS SageMaker, and Google Cloud AI Platform.
Yes, our AI/ML Fundamentals course is designed for both beginners and professionals looking to gain a foundational understanding of AI and machine learning. Advanced courses such as AI/ML Essentials and TensorFlow & PyTorch for AI are suitable for individuals with some experience in data science or cloud platforms.
Yes, our AI & Machine Learning Bootcamp and AI/ML in Production courses cover advanced topics such as deep learning, neural networks, model deployment, and AI scaling in the cloud. These courses include hands-on labs and real-world scenarios to prepare you for complex AI/ML projects.
Absolutely. We can tailor the curriculum to your specific industry, use cases, and cloud environments, ensuring your team learns the most relevant AI/ML concepts and practices.
Yes, all of our courses include hands-on labs where participants work with real-world datasets, build models, and deploy them in cloud environments using tools like TensorFlow, PyTorch, and cloud-native AI services.
We offer both online and in-person training options, allowing you to choose the format that best suits your needs.
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About us

We specialize in providing Cloud training and educational resources. Our mission is to empower organizations by enhancing their proficiency in Cloud technologies, covering a wide spectrum from foundational concepts to advanced applications.

  • 1701 Hollis St, Suite 800, Halifax, NS, Canada
  • [email protected]
  • Phone: +1 (902) 223-9135
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