The Artificial Intelligence course provides a comprehensive exploration of this cutting-edge field, covering topics such as Machine Learning, Neural Networks, NLP, and Computer Vision. Students will gain essential AI skills and ethical insights, driving innovation and contributing to AI advancements.




Course Price:
Original price was: £194.00.Current price is: £19.99.
Course Duration:
3 hours, 37 minutes
Total Lectures:
29
Total Students:
66
Average Rating:
2

Overview

The Artificial Intelligence course offers a comprehensive and in-depth exploration of this cutting-edge field. Students will be introduced to fundamental topics, beginning with an overview of Artificial Intelligence and its applications. Through subsequent modules, students will delve into Machine Learning, enabling computers to learn from data and make intelligent decisions.

The curriculum further explores Neural Networks, which mimic the human brain's learning process and form the backbone of various AI applications. Natural Language Processing (NLP) is covered, focusing on enabling machines to understand and interact with human language. Computer Vision is addressed, allowing machines to interpret and process visual information from the world around them.

Additionally, the course emphasizes the ethical considerations and societal implications of AI, ensuring students understand the responsible use and impact of this transformative technology. Upon completion of the Artificial Intelligence course, graduates will be well-equipped to apply AI techniques to various domains, contributing to advancements in technology and driving innovation in the ever-evolving AI landscape. With specialized knowledge in Machine Learning, Neural Networks, NLP, and Computer Vision, students will be prepared to explore diverse AI applications and contribute positively to the field of Artificial Intelligence.

What Will You Learn?

  • An introduction to Artificial Intelligence and its applications.
  • Machine Learning techniques, enabling computers to learn from data.
  • Neural Networks, mimicking the human brain's learning process.
  • Natural Language Processing (NLP) for understanding and interacting with human language.
  • Computer Vision for interpreting and processing visual information.
  • Ethical considerations and societal implications of AI.

Who Should Take The Course?

  • Aspiring AI researchers and developers.
  • Professionals seeking to enhance their AI knowledge and skills.
  • Individuals interested in the ethical implications of AI technology.
  • Students pursuing careers in data science and machine learning.
  • Anyone curious about the field of Artificial Intelligence and its real-world applications.

Requirements

  • Basic programming knowledge (preferably in Python).
  • Familiarity with mathematics and statistics concepts.
  • Understanding of data analysis and data manipulation techniques.
  • Some background in computer science or related fields is advantageous but not mandatory.

Course Curriculum

    • Definition of AI 00:07:00
    • Brief history of AI 00:05:00
    • AI applications and use cases 00:06:00
    • Introduction to Python programming language for AI 00:05:00
    • Introduction to supervised and unsupervised learning 00:06:00
    • Linear regression 00:07:00
    • Classification algorithms (logistic regression, decision trees, k-nearest neighbours) 00:05:00
    • Clustering algorithms (k-means, hierarchical clustering) 00:06:00
    • Introduction to neural networks 00:07:00
    • Feedforward neural networks 00:06:00
    • Convolutional neural networks (CNNs) 00:05:00
    • Recurrent neural networks (RNNs) 00:06:00
    • Deep learning and its applications 00:06:00
    • Introduction to NLP 00:06:00
    • Text pre-processing 00:07:00
    • Word embeddings (Word2Vec, GloVe) 00:06:00
    • Recurrent neural networks for NLP 00:06:00
    • Sentiment analysis and text classification 00:07:00
    • Introduction to computer vision 00:06:00
    • Image pre-processing 00:06:00
    • Convolutional neural networks for computer vision 00:06:00
    • Object detection and recognition 00:06:00
    • Image segmentation 00:06:00
    • AI and employment 00:06:00
    • Bias and fairness in AI 00:07:00
    • AI and privacy 00:05:00
    • Ethical considerations in AI research and development 00:05:00
    • Exam of Artificial Intelligence 00:50:00
    • Order Certificate 00:05:00

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