Certificate in Deep Learning for QA: Foundational Knowledge
-- ViewingNowThe Certificate in Deep Learning for QA: Foundational Knowledge is a comprehensive course designed to equip learners with essential skills in deep learning, specifically for Quality Assurance. This program emphasizes the importance of deep learning in modern QA, addressing industry demand for professionals with a strong understanding of these concepts.
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⢠Introduction to Deep Learning: Understanding the basics of deep learning, its applications, and benefits.
⢠Neural Networks: Exploring the structure and functionality of neural networks, including feedforward and recurrent networks.
⢠Convolutional Neural Networks (CNNs): Learning about CNNs, their architecture, and their use in image recognition and computer vision.
⢠Deep Learning Frameworks: Getting familiar with popular deep learning frameworks, such as TensorFlow, PyTorch, and Keras.
⢠Training and Optimization Techniques: Understanding optimization algorithms, training strategies, and regularization techniques.
⢠Transfer Learning and Fine-Tuning: Learning how to leverage pre-trained models, transfer learning, and fine-tuning.
⢠Natural Language Processing (NLP) with Deep Learning: Exploring NLP techniques and models based on deep learning.
⢠Generative Models and Applications: Delving into generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), and their applications.
⢠Evaluation Metrics and Best Practices: Measuring performance and adhering to best practices for deep learning models in QA.
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