AI ML with Deep Learning and Supervised Models

Coursera MOOC / Non-credit USD 49
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AI ML with Deep Learning and Supervised Models

About this course

This comprehensive AI ML with Deep Learning and Supervised Models specialization equips you with the skills to excel in roles across AI, machine learning, and deep learning. Through in-depth modules, you'll master regression, classification, clustering, neural networks, and advanced AI frameworks to solve real-world challenges. By the end of this course, you will be able to: Master AI and ML Fundamentals: Learn key AI concepts, machine learning techniques, and applications in supervised, unsupervised, and reinforcement learning. Build and Optimize Neural Networks: Develop feedforward, convolutional, and recurrent neural networks using TensorFlow and Keras for diverse applications. Implement RNNs and LSTMs: Apply advanced models like Recurrent Neural Networks and Long Short-Term Memory networks for sequential data tasks. Analyze AI's Transformative Impact: Understand ethical considerations, emerging trends, and AI’s potential to innovate across industries. Guided by industry experts, you’ll gain hands-on experience and practical knowledge, preparing you to leverage AI and machine learning technologies effectively in your career.

What you'll learn

  • understand key AI concepts
  • apply machine learning techniques
  • build neural networks using TensorFlow and Keras
  • implement advanced models like RNNs and LSTMs
  • analyze AI's ethical considerations and emerging trends

Course objectives

  • master AI and ML fundamentals
  • develop practical skills for solving real-world challenges
  • prepare for roles in AI and machine learning

Skills you'll gain

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