Artificial Intelligence

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Reed Courses Certificate of Completion

Digital certificate - Included

Final Exam

Included in course price

• Disclaimer 01:00

  • 1: Disclaimer 01:00

• Lecture 1: Introduction to Artificial Intelligence 08:00

  • 2: Lesson 1: Definition of AI 02:00
  • 3: Lesson 2: Brief history of AI 02:00
  • 4: Lesson 3: AI applications and use cases 02:00
  • 5: Lesson 4: Introduction to Python programming language for AI 02:00

• Lecture 2: Machine Learning 08:00

  • 6: Lesson 1: Introduction to supervised and unsupervised learning 02:00
  • 7: Lesson 2: Linear regression 02:00
  • 8: Lesson 3: Classification algorithms... 02:00
  • 9: Lesson 4: Clustering algorithms (k-means, hierarchical clustering) 02:00

• Lecture 3: Neural Networks 10:00

  • 10: Lesson 1: Introduction to neural networks 02:00
  • 11: Lesson 2: Feedforward neural networks 02:00
  • 12: Lesson 3: Convolutional neural networks (CNNs) 02:00
  • 13: Lesson 4: Recurrent neural networks (RNNs) 02:00
  • 14: Lesson 5: Deep learning and its applications 02:00

• Lecture 4: Natural Language Processing (NLP) 10:00

  • 15: Lesson 1: Introduction to NLP 02:00
  • 16: Lesson 2: Text pre-processing 02:00
  • 17: Lesson 3: Word embeddings (Word2Vec, GloVe) 02:00
  • 18: Lesson 4: Recurrent neural networks for NLP 02:00
  • 19: Lesson 5: Sentiment analysis and text classification 02:00

• Lecture 5: Computer Vision 08:00

  • 20: Lesson 1: Introduction to computer vision 01:00
  • 21: Lesson 2: Image pre-processing 02:00
  • 22: Lesson 3: Convolutional neural networks for computer vision 02:00
  • 23: Lesson 4: Object detection and recognition 01:00
  • 24: Lesson 5: Image segmentation 02:00

• Lecture 6: Ethics and Societal Implications of AI 08:00

  • 25: Lesson 1: AI and employment 02:00
  • 26: Lesson 2: Bias and fairness in AI 02:00
  • 27: Lesson 3: AI and privacy 02:00
  • 28: Lesson 4: Ethical considerations in AI research and development 02:00

• Assessment 10:00

  • 29: Final Exam 10:00

The Artificial Intelligence course offers an in-depth exploration of AI fundamentals and advanced techniques, designed to provide a well-rounded understanding of this cutting-edge field. You will begin with an introduction defining artificial intelligence, tracing its history, and examining its wide-ranging applications across industries.

The course introduces the Python programming language as a foundational tool for AI development, ensuring you gain hands-on experience in coding. You will explore machine learning, including supervised and unsupervised learning methods such as linear regression, classification algorithms, and clustering techniques, enabling you to build predictive models and analyse data effectively.

Neural networks are covered extensively, including feedforward, convolutional (CNN), and recurrent (RNN) architectures, culminating in deep learning and its transformative applications. The natural language processing (NLP) module teaches text pre-processing, word embeddings, recurrent networks for language tasks, and sentiment analysis, helping you understand how machines interpret human language.

Computer vision lessons cover image pre-processing, CNN applications, object detection, recognition, and image segmentation, equipping you with skills to develop AI systems that perceive and interpret visual data. The course also addresses ethical and societal implications of artificial intelligence, including AI’s impact on employment, bias and fairness, privacy concerns, and responsible research and development.

Certification
Upon successfully completing this artificial intelligence course, you will receive a free digital certificate recognising your achievement. Provided by Course Line, an award-winning educational brand, this training delivers industry-standard knowledge to support your career in AI.

This artificial intelligence course is ideal for individuals interested in entering the AI field or enhancing their understanding of AI technologies and applications. It suits beginners with little to no prior programming experience, as well as professionals seeking to deepen their technical and theoretical knowledge of AI.

Students and career changers interested in data science, software development, or technology innovation will find this course a practical and accessible introduction. Adult learners returning to education benefit from the flexible online format that allows balancing study with personal and professional commitments.

This course is also suitable for IT professionals, business analysts, and innovators aiming to apply AI solutions within their industries, fostering a strong foundation in artificial intelligence concepts and ethical considerations.

Learners should have basic written English proficiency to fully engage with course content. No prior programming or AI experience is necessary, though a keen interest in technology and mathematics is helpful. A reliable internet connection and access to a computer or compatible device are required for effective online study. Commitment and self-motivation are important to complete this self-paced artificial intelligence programme.

Graduates can pursue roles such as AI developer, machine learning engineer, data analyst, AI researcher, or software engineer specializing in artificial intelligence applications. This course also provides a foundation for advanced studies and specialisation in AI, data science, robotics, and related fields, opening pathways to innovative and high-demand technology careers.

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