Certified Specialist Programme in Deep Learning for Recommendation Systems
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2个月完成
每周2-3小时
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课程详情
- Foundations of Deep Learning for Recommendation Systems
- Recommender Systems Architectures: Collaborative Filtering & Content-Based Filtering
- Deep Learning Models for Recommendations: Autoencoders & Restricted Boltzmann Machines
- Advanced Deep Learning Models: Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) Networks for sequential recommendations
- Embedding Methods & Matrix Factorization Techniques
- Handling Sparsity and Cold Start Problems in Recommendation Systems
- Evaluation Metrics and A/B Testing for Recommendation Systems
- Deployment and Scalability of Deep Learning Recommendation Systems
职业道路
Career Role Description Deep Learning Engineer (Recommendation Systems) Develop and deploy cutting-edge recommendation algorithms using deep learning techniques.
High demand for expertise in TensorFlow/PyTorch.
Machine Learning Scientist (Recommendation Systems) Research and develop novel deep learning models to improve recommendation accuracy and personalization.
Requires strong mathematical background and research skills.
Data Scientist (Recommendation Systems) Analyze large datasets, build predictive models using deep learning for recommendation systems, and communicate findings to stakeholders.
Strong data visualization skills essential.
AI/ML Consultant (Recommendation Systems) Advise clients on the implementation and optimization of deep learning-based recommendation systems.
Excellent communication and problem-solving skills are vital.
入学要求
- 对主题的基本理解
- 英语语言能力
- 计算机和互联网访问
- 基本计算机技能
- 完成课程的奉献精神
无需事先的正式资格。课程设计注重可访问性。
课程状态
本课程为职业发展提供实用的知识和技能。它是：
- 未经认可机构认证
- 未经授权机构监管
- 对正式资格的补充
成功完成课程后，您将获得结业证书。
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