AI Programming with Python
Concepts Covered: Python, NumPy, Pandas, Matplotlib, PyTorch
AI is one of the most transformational and fastest-growing technologies of our time, with its market value expected to exceed $190 billion by 2025. In just three months, you can complete AI courses and advance your career in this revolutionary field.
Concepts Covered: Python, NumPy, Pandas, Matplotlib, PyTorch
Concepts Covered: Momentum Trading Strategy, Smart Beta, Alpha Factors, Natural Language Processing, Deep Learning, Neural Networks
Concepts Covered: API Development, Automated Model Scoring, CI/CD, Model Testing, Data Version Control, Machine Learning Pipelines
Concepts Covered: Neural Networks, Perceptron, Autoencoders, Convolutional Neural Networks, PyTorch, Object Detection, Recurrent Neural Networks, Long-Short Term Memory Networks, Backpropagation, Generative Adversarial Networks, Deep Learning Techniques, Image Generation, Hyperparameter Tuning
Concepts Covered: Reinforcement Learning, Neural Networks, PyTorch, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG)
Concepts Covered: Convolutional Neural Networks, Recurrent Neural Networks, Simultaneous Localization and Mapping, Object Tracking, Image Classification, Deep Learning
Concepts Covered: Machine Learning, Speech Recognition, Sentiment Analysis, Machine Translation, Part of Speech Tagging
Concepts Covered: Feature Engineering, Machine Learning Fluency, Data Loading with SageMaker, Amazon S3, Neural Network Basics, Deep Learning Fluency, Hyperparameter Tuning, Machine Learning Framework Fundamentals, SageMaker JumpStart, Cloud Resource Allocation, Distributed Model Training with SageMaker, AWS Lambda
Concepts Covered: AI Products, Training ML Models, Annotating Datasets, Prototyping a Product
Concepts Covered: Artificial Intelligence, Machine Learning, Business Strategy, Data Labeling, Data Modeling
Concepts Covered: Constraint Propagation, AI Algorithms, Constraint Satisfaction Problems, Backtracking Search, Optimization Algorithms, Search Algorithms, Minimax Search, Bayesian Networks, Planning, Pattern Recognition, Time-Series Analysis with ML
Concepts Covered: Artificial Intelligence, 2D Medical Imaging, 3D Medical Imaging, Electronic Health Record Data, Deep Learning, Wearable Device Data, Supervised Learning
Concepts Covered: Introduction to Machine Learning, Supervised Learning, Deep Learning, Unsupervised Learning
Concepts Covered: TensorFlow, Deep Learning, scikit-learn, Supervised Learning, Unsupervised Learning
Concepts Covered: Portfolio Websites, Professional Networking, Resumes, Social Media Presence, Non-Disclosure Agreements, Service Agreements, Freelance Pricing Frameworks, Invoicing, Brand Design, Elevator Pitches, Formal Written Communication, Project Management tools, Project Scoping
Concepts Covered: Azure Machine Learning, Azure Machine Learning SDK, Automation with Pipelines, Automated ML, Machine Learning Operations
Concepts Covered: Object Detection, Image Classification, Form Recognition, Facial Recognition, Face Detection, Azure Cognitive Services, Microsoft Bot Framework, Azure Conversational AI Agents, Architecture Diagramming, Requirements Gathering, Intent Recognition, Key Phrase Extraction, Azure Form Recognizer, Bounding Boxes
Concepts Covered: Introduction to Machine Learning, Unsupervised Learning
Concepts Covered: Introduction to Machine Learning, Supervised Learning
Concepts Covered: SLAM, Object Localization, Object Tracking, Feature Matching
Concepts Covered: Alexa Skill Creation, Voice User Interfaces, Alexa Skill Deployment, Feature Extraction, Speech Recognition
Concepts Covered: Recurrent Neural Networks, Attention Mechanisms, Neural Network Memory, Long-Short Term Memory Networks, Convolutional Neural Networks, Image Caption generation, YOLO Algorithm, Model Training
Concepts Covered: Machine Learning Pipelines, MLOps, Machine Learning Methods, Machine Learning Frameworks, Computer Science and Programming, Software Development Processes, AI and Machine Learning Tools, Data Engineering, Data Analysis, Python
Concepts Covered: Neural Networks, Training Neural Networks, Perceptron, Overfitting Prevention, Advanced Probability, Gradient Descent
Concepts Covered: Generative Adversarial Networks, Deep Learning Techniques, Deep Learning Model Optimization, CycleGAN, Hyperparameter Tuning, Model Evaluation, Image Generation, Markov Games
Concepts Covered: AI Fairness, AI Governance, AI Transparency, Model Bias Analysis, Model Bias Mitigation, Explainable AI, Ethical AI
Machine learning is becoming a fundamental skill as software development is entering a new era. This path will enable you to start a career as a machine learning engineer. First learn the fundamentals of programming in Python, linear algebra, and neural networks, and then move on to core machine learning concepts.
TensorFlow, Deep Learning, scikit-learn, Supervised Learning, Unsupervised Learning
Learn moreIntroduction to Machine Learning, Supervised Learning, Deep Learning, Unsupervised Learning
Learn morePython, NumPy, Pandas, Matplotlib, PyTorch
Learn moreFeature Engineering, Machine Learning Fluency, Data Loading with SageMaker, Amazon S3, Neural Network Basics, Deep Learning Fluency, Hyperparameter Tuning, Machine Learning Framework Fundamentals, SageMaker JumpStart, Cloud Resource Allocation, Distributed Model Training with SageMaker, AWS Lambda
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