AI vs. Machine Learning vs. Deep Learning Course

The Oxford Training Centre presents an in-depth course titled AI vs. Machine Learning vs. Deep Learning course is designed to unravel the complexities of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). This one-week training program is tailored for professionals and enthusiasts seeking to explore Natural Language Processing (NLP) and its applications across various domains. Participants will gain hands-on experience in NLP algorithms, text mining, and natural language understanding using tools like Python.

Objectives and target group

Objectives

This course aims to:

1. Distinguish AI, ML, and DL: Understand the core differences and connections between these key areas of technology.
2. Explore NLP Fundamentals: Learn the basics of natural language processing, including algorithms, tools, and techniques.
3. Hands-on Training: Engage in practical NLP projects to solidify theoretical concepts.
4. Master NLP Tools: Gain expertise in NLP with Python, text mining, and deep learning applications for natural language understanding.
5. Develop Real-World Applications: Build skills to implement NLP applications in industries such as healthcare, finance, and customer service.

Target Group

This course is ideal for:

• Professionals in AI and Machine Learning: Enhance your understanding of NLP applications in AI workflows.
• Data Scientists and Analysts: Expand your knowledge of machine learning and deep learning techniques applied to text mining and NLP.
• IT and Software Engineers: Gain hands-on experience with NLP tools and techniques.
• Students and Enthusiasts: Start your journey with an introduction to NLP and obtain certification to enhance your career prospects.
• Industry Leaders and Managers: Understand the potential of NLP projects to innovate business processes and customer experiences.

Content

This intensive course covers the following:

Module 1: Foundations of AI, ML, and DL

• Overview of AI, ML, and DL: Core concepts and differences.
• Evolution of AI and its integration with natural language processing.

Module 2: Natural Language Processing Fundamentals

• Introduction to NLP: Key concepts and techniques.
• NLP Algorithms: Tokenization, stemming, lemmatization, and more.
• Understanding Natural Language vs. Natural Language Generation.

Module 3: Hands-On NLP Training with Python

• Python for NLP: Libraries and frameworks.
• Building text mining models.
• Exploring machine learning and NLP integration.

Module 4: Advanced NLP Techniques and Applications

• Deep Learning for NLP: Techniques and architectures.
• Real-world NLP projects: Chatbots, sentiment analysis, and more.
• Practical applications in various industries, including healthcare, e-commerce, and finance.

Module 5: Certification and Final Project

• Final assessment: Develop a complete NLP application.
• NLP certification awarded by Oxford Training Centre upon completion.