Neural Networks Courses and Certifications

Edureka Career Certificate

Mastering AI: Neural Nets, Vision System, Speech Recognition

8 ratings at Coursera

Master essential AI concepts and practical skills in neural networks, computer vision, and speech recognition through hands-on projects and real-world applications using Python.

• Coursera
• 16 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 4 courses

Large Language Models (Using Huggingface) (Live Online)

8 ratings at CourseHorse

Tap into the capabilities of large language models using Hugging Face in this comprehensive 3-day course.

• CourseHorse
• 20 hours
• Self-Paced
• $1,495.00

Packt Career Certificate

Deep Learning with Real-World Projects

7 ratings at Coursera

Master deep learning through hands-on projects. Apply neural networks, CNNs, and transfer learning to real-world scenarios using TensorFlow and Keras. Build a portfolio showcasing expertise in AI development.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course

Packt Career Certificate

Building with OpenAI API

7 ratings at Coursera

Master GPT models and OpenAI API to build AI-powered Python applications, from prompt engineering to deploying serverless functions and interactive tools.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Packt Career Certificate

Deep Learning with TensorFlow

6 ratings at Coursera

Master deep learning with TensorFlow through ANNs, RNNs, and CNNs. Build models for image classification, time series prediction, and NLP using real datasets and optimization techniques.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Career Certificate

Introduction to Transformer Models for NLP

5 ratings at Coursera

Master transformer architectures like BERT, GPT, and T5 through hands-on coding exercises. Build attention mechanisms, apply transfer learning, and fine-tune models for real-world NLP applications.

• Coursera
• 4 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 3 courses

Predictive Analytics

Gain insights into predictive analytics with Python, learning to build models, diagnose performance issues, leverage advanced techniques like neural networks, and integrate data-driven insights into decision-making for digital transformation.

• Coursera
• 1 day 23 hours 19 minutes
• Self-Paced
• Paid Course

Ethics and Governance in the Age of Generative AI

Explore ethical and technical aspects of generative AI, including responsible development, bias reduction, and governance strategies. Gain insights into AI model deployment and societal impacts.

• Coursera
• 1 day 2 hours 43 minutes
• Self-Paced
• Paid Course

Machine Learning

Master Python-based machine learning from fundamentals to deep learning, covering scikit-learn, TensorFlow, neural networks, and real-world applications with text and image data.

• Coursera
• 1 day 12 hours 2 minutes
• Self-Paced
• Paid Course

Generative AI: Foundations and Concepts

Explore the mathematical foundations of generative AI, from neural networks to advanced deep learning models, with practical implementation techniques and applications in engineering.

• Coursera
• 21 hours 36 minutes
• Self-Paced
• Paid Course

NLP in Engineering: Concepts & Real-World Applications

Master practical NLP techniques and their engineering applications through word embeddings, neural networks, and deep learning models. Implement advanced methods for real-world problem-solving in natural language processing.

• Coursera
• 13 hours 28 minutes
• Self-Paced
• Paid Course

Applied Natural Language Processing in Engineering Part 1

Discover NLP fundamentals from text classification to neural networks, optimization techniques, word embeddings, and parsing methods for engineering applications.

• Coursera
• 1 day 3 hours 45 minutes
• Self-Paced
• Paid Course

Generative AI Part 1

Explore the theoretical foundations of generative AI, covering neural networks, transformers, LLMs, optimization, and real-world applications across various fields.

• Coursera
• 25 hours
• Self-Paced
• Paid Course

Deep Learning for AI Part 1

Master the foundations of deep learning—from neural networks and CNNs to RNNs, VAEs, GANs, and Transformers—with hands-on TensorFlow/Keras and PyTorch implementation.

• Coursera
• 7 weeks, 3 hours a week
• Self-Paced
• Paid Course

Generative AI Part 2

Explore advanced generative AI concepts including transformers, VAEs, GANs, diffusion models, and normalizing flows, with emphasis on mathematical foundations and real-world applications.

• Coursera
• 22 hours
• Self-Paced
• Paid Course