Packt

AI Engineer Associate 专项课程

Packt

AI Engineer Associate 专项课程

Master AI, Machine Learning, and Deep Learning.

Learn to implement AI algorithms, build deep learning models, & create AI agents for real-world use.

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深入学习学科知识
中级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
中级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Master advanced machine learning algorithms like ensemble learning, boosting, and XGBoost.

  • Implement deep learning models with TensorFlow and PyTorch to solve real-world problems.

  • Develop and deploy AI agents across multiple industries, including healthcare, finance, and robotics.

  • Gain hands-on experience with neural networks, feature engineering, and model evaluation techniques.

要了解的详细信息

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授课语言:英语(English)
最近已更新!

February 2026

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

  • 向大学和行业专家学习热门技能
  • 借助实践项目精通一门科目或一个工具
  • 培养对关键概念的深入理解
  • 通过 Packt 获得职业证书

专业化 - 3门课程系列

Machine Learning Foundations

Machine Learning Foundations

第 1 门课程 7小时

您将学到什么

  • Gain hands-on experience implementing machine learning algorithms like regression, decision trees, and neural networks in Python.

  • Understand and apply feature engineering techniques to optimize data for machine learning models.

  • Master model evaluation methods, including cross-validation and hyperparameter tuning, to enhance model performance.

  • Explore advanced machine learning techniques such as reinforcement learning, neural networks, and unsupervised learning methods.

您将获得的技能

类别:Python Programming
类别:Recurrent Neural Networks (RNNs)
类别:Model Evaluation
类别:Unsupervised Learning
类别:Dimensionality Reduction
类别:Data Preprocessing
类别:Reinforcement Learning
Deep Learning and Advanced Techniques

Deep Learning and Advanced Techniques

第 2 门课程 9小时

您将学到什么

  • Gain expertise in ensemble learning techniques like bagging, boosting, and gradient boosting to improve model accuracy.

  • Build and optimize neural networks using TensorFlow, Keras, and PyTorch for deep learning tasks.

  • Apply advanced techniques like transfer learning, fine-tuning, and handling complex data types.

  • Deploy deep learning models to production environments and troubleshoot performance issues.

您将获得的技能

类别:PyTorch (Machine Learning Library)
类别:Deep Learning
类别:Model Deployment
类别:Artificial Neural Networks
类别:Transfer Learning
类别:Applied Machine Learning
类别:Machine Learning Methods
类别:Tensorflow
类别:Performance Tuning
类别:Model Evaluation
类别:Convolutional Neural Networks
类别:Application Frameworks
类别:Keras (Neural Network Library)
AI Engineering and Deployment

AI Engineering and Deployment

第 3 门课程 9小时

您将学到什么

  • Master machine learning models using TensorFlow, Keras, and pre-trained neural networks for various tasks.

  • Build and deploy AI agents with advanced frameworks like AutoGPT, IBM Bee, and LangGraph.

  • Learn the ethical, legal, and societal implications of AI technologies.

  • Gain hands-on experience in deploying AI models to production environments using TensorFlow Serving and Kubernetes.

您将获得的技能

类别:Model Deployment
类别:Tensorflow
类别:Artificial Intelligence
类别:Machine Learning
类别:Transfer Learning
类别:Applied Machine Learning
类别:Agentic systems
类别:BeeAI
类别:Keras (Neural Network Library)
类别:Convolutional Neural Networks
类别:Deep Learning
类别:Scalability
类别:AI Security
类别:Responsible AI
类别:Recurrent Neural Networks (RNNs)

获得职业证书

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位教师

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