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Natural Language Processing: A 3-Step Process to Master NLP
Highest Rated
Rating: 4.6 out of 5(14 ratings)
835 students

Natural Language Processing: A 3-Step Process to Master NLP

Master Natural Language Processing with Practical Skills to Build Real-World NLP Applications
Highest Rated
Created byDr. Chris Mall • 40,000+ Students Worldwide
Last updated 11/2024
English
English [Auto],

What you'll learn

  • Master Essential NLP Concepts: Understand the core principles of Natural Language Processing, including text preprocessing, tokenization, and language models.
  • Build Real-World NLP Applications: Gain hands-on experience developing NLP solutions like sentiment analysis, text classification, and named entity recognition.
  • Work with Transformer Models: Learn to implement and fine-tune state-of-the-art transformer models such as ChatGPT and Gemini for advanced NLP tasks.
  • Apply NLP in Practical Scenarios: Develop the skills to apply NLP techniques to real-world challenges in business, research, and build a portfolio of projects.

Course content

3 sections • 16 lectures • 4h 13m total length

  • Introduction to Artificial Intelligence and Natural Language Processing2:11

    Explore artificial intelligence foundations, including expert systems, NLP, speech recognition, and machine vision, and the four AI types—reactive, memory, theory of mind, and self-awareness.

  • Let's see Artificial Intelligence in Practice16:45

    Demonstrate training image, sound, and pose models with Teachable Machine, test in real time, export to web or Android, and explore key ai tools for NLP and beyond.

  • 3 stories for how AI began - Alan Turing - Gary Kasparof21:09

    Explore Alan Turing’s legacy, the Turing test, and milestones with Kasparov, Deep Blue, and AlphaZero, highlighting reinforcement learning, machine learning, and the evolution of natural language processing.

  • Introduction to Machine Learning10:45

    Explore how machines learn through training and testing, using supervised, unsupervised, and reinforcement learning to solve tasks like spam filtering, house-price prediction, clustering, and robotics.

  • An Agent for Psychologists17:56

    Explore how AI tools, including chatbots and virtual therapists, support psychologists with early detection, sentiment analysis, and personalized therapy from speech, text, and nonverbal cues.

  • Differences between Artificial Intelligence, Machine Learning and Data Science6:27

    Differentiate data science, machine learning, and artificial intelligence by examining data modeling, warehousing, and AI's use of deep learning and natural language processing.

  • Common Artificial Intelligence Workloads. Machine Learning, NLP, Computer Vision1:09

    Explore common AI workloads, including machine learning, anomaly detection, computer vision, NLP, and conversational AI, with a focus on interpreting data, patterns, and human language.

  • What is Natural Language Processing1:25

    Explore natural language processing and how Azure workloads enable machines to read, understand, and derive meaning from human language, with text analysis, entity recognition, sentiment analysis, and translation.

  • What is Conversational AI?2:47

    Explore the fundamentals of conversational AI, including dialogue with bots across text and voice channels, and the role of design, context, and intent understanding in human-like interactions.

Requirements

  • No Prior NLP Experience Required: This course is designed for beginners, so no prior knowledge of Natural Language Processing is needed.
  • Basic Python Knowledge: Familiarity with Python programming is helpful but not mandatory. We'll cover any necessary Python concepts along the way.
  • A Computer with Internet Access: You'll need a laptop or desktop computer to follow along with the coding exercises and install required libraries.
  • A Desire to Learn: Enthusiasm for exploring NLP and applying it to real-world problems is all you need to get started!

Description

Are you ready to dive into the world of Natural Language Processing (NLP) and learn how to elevate the power of human language in your applications? Whether you want to understand how chatbots work, analyze customer sentiment, or automate text analysis, NLP is an essential skill in today’s AI-driven world. "Natural Language Processing: A 3-Step Process to Master NLP" is your comprehensive guide to unlocking the full potential of NLP.

This course offers a hands-on, practical approach to mastering NLP techniques. Whether you're a beginner or an experienced developer, this course will guide you from the foundational concepts to building real-world NLP projects. You will not only learn the theory but also apply it through practical exercises and projects designed to make you industry-ready.

Course Highlights:

  • Real-world projects to build your portfolio

  • Comprehensive coverage of both traditional and modern NLP techniques

  • Hands-on coding exercises with popular libraries

  • In-depth explanations of key algorithms and models

By the end of this course, you will be equipped with the knowledge and skills needed to apply NLP techniques to real-world challenges. Whether your goal is to enhance your existing applications or embark on a new career path, this course will set you on the right track.

Don’t wait—unlock the power of language data and take your first step towards becoming an NLP expert today!

Who this course is for:

  • Beginners who are new to Natural Language Processing (NLP) and want to learn the fundamentals in a hands-on, practical way.
  • Developers and Data Scientists looking to expand their skill set by incorporating NLP into their projects and workflows.
  • AI Enthusiasts who are eager to explore how language data is processed and used to build intelligent applications like chatbots, sentiment analyzers, and more.
  • Entrepreneurs and Product Managers interested in integrating NLP technology into their products, enhancing user experiences, or automating text-based tasks.
  • Students and Researchers seeking to build a strong foundation in NLP to pursue advanced studies or contribute to academic and industry-related projects.

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