AI Data Science Engineering - NLP - eLearning Bundle CourseNew

Welcome to the AI Data Science Engineering - NLP master bundle, your definitive pathway to becoming a leader in the rapidly evolving field of Natural Language Processing (NLP). This extensive bundle is meticulously designed for Data Scientists, Machine Learning Engineers, and AI Developers who aspire to master the complexities of human language processing, from foundational theories to cutting-edge generative AI and Large Language Models (LLMs).

In today's intelligent systems, the ability to understand, process, and generate human language is paramount. This bundle provides you with the comprehensive knowledge and hands-on skills required to excel. You will delve deep into Natural Language Processing with Python, exploring essential libraries like NLTK, SpaCY, Gensim, and Huggingface. Gain expertise in crucial NLP techniques such as text preprocessing, tokenization, word embeddings, sentiment analysis, text summarization, and topic modeling. The bundle also covers the revolutionary Transformers architecture and its applications in generative AI, including LLMs, machine translation, and conversational AI. You'll work with powerful deep learning frameworks like PyTorch to build neural networks, including RNNs and LSTMs, and even create practical applications like chatbots and neural translation machines. Through real-world projects, you'll learn to solve complex language-related problems, design effective prompts, and integrate advanced RAG (Retrieval-Augmented Generation) techniques for enhanced AI model performance.

What You Will Gain:

Comprehensive NLP Mastery: Develop a profound understanding of NLP from its basic concepts and mathematical foundations to advanced techniques for text processing and analysis.
Practical Python for NLP: Gain hands-on proficiency in Python for NLP, utilizing a wide array of libraries and tools including NLTK, SpaCY, Gensim, Flair, Huggingface, and OpenAI APIs.
Deep Learning for Language Models: Master the application of deep learning frameworks (PyTorch) to build and optimize neural networks, RNNs, LSTMs, and sequence-to-sequence models for various NLP tasks.
Transformer Models & Generative AI: Understand the architecture and implementation of Transformers, apply them to generative AI tasks, including text-to-image, and gain expertise in fine-tuning Large Language Models (LLMs).
Real-World NLP Project Development: Build practical NLP applications such as sentiment analyzers, neural translation machines, chatbots (with Rasa), spam detectors, and text recommender systems.
Text Preprocessing & Feature Engineering: Learn advanced techniques for text preprocessing, including tokenization, stemming, lemmatization, stopword removal, and vectorization methods like Bag of Words, TF-IDF, and various word embeddings.
Advanced AI Integration: Explore prompt engineering for optimizing AI model performance, utilize vector databases for efficient data retrieval, and apply advanced RAG techniques to integrate external knowledge sources.

Why This Bundle?

The AI Data Science Engineering - NLP bundle is ideal for ambitious Data Scientists, Machine Learning Engineers, AI Developers, and NLP Specialists eager to excel in the burgeoning field of conversational AI, generative models, and intelligent language understanding. If you aim to build advanced AI systems that interact seamlessly with human language, from sentiment analysis to developing custom LLMs, this bundle provides the in-depth knowledge and hands-on projects needed to lead innovation. Elevate your career by mastering the skills that are redefining how humans and machines communicate.

Unlock the Power of Language with AI.Enroll in the AI Data Science Engineering - NLP bundle today and build the intelligent language systems of tomorrow!

Also Included - 4 Courses: An Essential Career Skills Pack with 4 courses in key areas for career management and growth, including Time Management, Digital Skills, Creativity and Soft Skills.

Course Notes

Important Course Information

This is a Lecture-Only eLearning Course. If you would like to practice any hands-on activities, you must use your own software.

Course Objectives:

Master Natural Language Processing (NLP) Fundamentals:
- Understand core NLP concepts, mathematical foundations, and their application in processing and analyzing human language.
Develop Advanced Python NLP Skills:
- Gain hands-on expertise with key Python libraries and tools for NLP, including NLTK, SpaCY, Gensim, Flair, Huggingface, and OpenAI APIs.
Build Deep Learning Models for NLP:
- Design, implement, and train neural networks (RNNs, LSTMs), sequence-to-sequence models, and other deep learning architectures using PyTorch for various NLP tasks.
Implement Transformer Models and Generative AI:
- Understand the architecture and capabilities of Transformers, apply them for generative AI tasks, including fine-tuning Large Language Models (LLMs), machine translation, and conversational AI.
Perform Comprehensive Text Preprocessing and Feature Engineering:
- Master techniques like tokenization, stemming, lemmatization, stopword removal, Bag of Words, TF-IDF, and various word embeddings.
Develop Real-World NLP Applications:
- Build practical projects such as sentiment analyzers, neural translation machines, chatbots, spam detectors, text summarizers, topic models, and text recommender systems.
Apply Advanced AI Techniques for Language Understanding:
- Learn prompt engineering, utilize vector databases, and implement Retrieval-Augmented Generation (RAG) for optimizing AI model performance and integrating external data.

Target Audience

Data Scientists: Professionals aiming to specialize in Natural Language Processing, generative AI, and Large Language Models.
Machine Learning Engineers: Engineers looking to deepen their expertise in NLP frameworks (PyTorch, TensorFlow) and apply advanced language models.
AI Developers: Developers focused on building intelligent systems that interact with and understand human language.
NLP Specialists: Current NLP practitioners seeking to update their skills with the latest advancements in Transformers, LLMs, and generative AI.
Software Engineers: Engineers interested in integrating sophisticated NLP and generative AI capabilities into their applications.
Researchers in AI/NLP: Academics and researchers seeking practical implementation skills for cutting-edge language technologies.
Anyone with a solid understanding of Python and AI/ML basics who wants to become proficient in Natural Language Processing and generative AI.

Key Features

Audio Narration
Video
Inline Activities

Exercises
Quizzes
Supplemental Resources

Languages

Audio/Video/Course Text: English.
Subtitles (Closed Caption): N/A.

Course Duration

AI Data Science Engineering - NLP: 100 hrs 58 min

Essential Career Skills Pack: 2 hrs 23 min

eLearning Training Delivery Method

Learn at Your Own Pace

This self-paced online course lets you learn independently at your own pace through Certstaffix Training's easy-to-use platform.

How It Works

A Learn at your own pace - Start and stop as it is convenient for you. Pick up where you left off.

Lecture utilizing video and recorded screenshots

6-month subscription length

Instant Access After Purchase

Have more than 10 students needing this course? Contact Us for bulk pricing.

Course Topics

Natural Language Processing in Python for Beginners

Course Duration - 23 hrs 31 min

Natural Language Processing (NLP), a subdivision of Artificial Intelligence (AI), is the ability of a computer to understand human language the way it’s spoken and written. Human language is typically referred to as natural language.

Humans also have different sensors. For instance, ears perform the function of hearing and eyes perform the function of seeing. Similarly, computers have programs for reading and microphones for collecting audio. Just as the human brain processes an input, a computer program processes a specific input. And during processing, the program converts the input to code that the computer understands.

This course, Natural Language Processing (NLP), Theory and Practice in Python, introduces you to the concepts, tools, and techniques of machine learning for text data. You will learn the elementary concepts as well as emerging trends in the field of NLP. You will also learn about the implementation and evaluation of different NLP applications using deep learning methods.

Code bundles are available here.

Course Objectives:

Identify language models and their uses in speech recognition
Use software tools such as SpaCY, NLTK, Gensim, and PyTorch
Identify the concepts of deep learning theory
Utilize linear subspaces for word embeddings
Identify the architecture of neural networks

Natural Language Processing with Real World Projects

Course Duration - 14 hrs 56 min

You will learn how machine can be trained to make sense of language humans use to interact. You will come across many NLP algorithms that teach the computational models about Lexical processing, basic syntactic processing. You will learn the mechanism Google translator uses, to understand the context of language and converts to a different language. You will build a chat-bot using an open-source tool Rasa, which is a text and voice-based conversations, understand messages, hold conversations, and connect to messaging channels and APIs. You will also learn to train the model you have created on NLU. The machine cannot be trained to understand or process data by traditional hand coded programs that rely heavily on very specific conditions. The moment there is a change in input, the hand coded program is rendered useless. So, rather than having to code possible conversations, we require a model that enables the system to make sense of context. By the end of the course you will be able to build NLP models that can summarize blocks of text to extract most important ideas, sentiment analysis to extract the sentiments from given block of text, identification of type entity extracted. All the projects included in this course are Real-World projects.

Course Objectives:

Identify speech and writing patterns to communicate with computer systems in a faster, easier and more convenient way
Describe how to train a chatbot
Explain Google translator

PyTorch Ultimate 202: From Basics to Cutting-Edge

Course Duration - 17 hrs 36 min

Dive into the ultimate PyTorch learning journey! Start with foundational concepts and progress to advanced AI models like CNNs, GANs, and Transformers. Master machine learning with practical coding exercises and real-world projects designed for modern professionals.

Course Objectives:

Build neural networks from scratch using PyTorch fundamentals
Implement CNNs for image and audio classification tasks efficiently
Explore GANs and RNNs for advanced generative and sequential modeling
Optimize models with hyperparameter tuning and performance evaluation
Deploy machine learning models using Flask and cloud platforms
Apply transfer learning for leveraging pre-trained AI models effectively

Hands-On Natural Language Processing with PyTorch

Course Duration - 2 hrs 24 min

The main goal of this course is to train you to perform complex NLP (Natural Language Processing) tasks (and build intelligent language applications) using Deep Learning with PyTorch.

You will build two complete real-world NLP applications throughout the course. The first application is a Sentiment Analyzer that analyzes data to determine whether a review is positive or negative towards a particular movie. You will then create an advanced Neural Translation Machine that is a speech translation engine, using Sequence to Sequence models with the speed and flexibility of PyTorch to translate given text into different languages.

By the end of the course, you will have the skills to build your own real-world NLP models using PyTorch's Deep Learning capabilities.

The code bundle for this video course is available here.

This course uses Python 3.6, Pytorch 1.0, NLTK 3.3.0, and Spacy 2.0 , while not the latest version available, it provides relevant and informative content for legacy users of PyTorch.

Course Objectives:

Process insightful information from raw data using NLP techniques with PyTorch
Work with PyTorch to take advantage of its maximum speed and flexibility
Define traditional and modern NLP methods and tools like NLTK, Spacy, Word2Vec, and Gensim
Implement a word embedding model and using it with the Gensim toolkit
Review sequence-to-sequence models (used in translation) that read one sequence and produce another
Identify usage of LSTMs using PyTorch for Sentiment Analysis and how it's different from RNNs
Compare and analyze results using attention networks to improve your project’s performance

Natural Language Processing - Probability Models in Python

Course Duration - 5 hrs 11 min

This comprehensive course guides technical professionals through essential NLP techniques using Python. Learn to detect spam, analyze sentiment, and perform text summarization and topic modeling. Gain hands-on experience with advanced methods and practical exercises to build robust NLP models.

Course Objectives:

Identify and implement spam detection algorithms
Conduct sentiment analysis using logistic regression
Perform text summarization using various methods
Apply advanced techniques like TextRank for summarization
Implement topic modeling with LDA and NMF
Utilize Latent Semantic Analysis in Python projects

Natural Language Processing - Embeddings and Text Preprocessing in Python

Course Duration - 6 hrs 8 min

Learn the concepts of NLP with a focus on text preprocessing and embeddings in Python. This course covers everything from basic definitions and tokenization to advanced techniques like TF-IDF and neural word embeddings. Gain practical coding skills through detailed demos and interactive exercises.

Course Objectives:

Apply basic text preprocessing techniques
Implement Bag of Words, Count Vectorizer, and TF-IDF models
Conduct stemming, lemmatization, and stopword removal
Explore vector similarity and word-to-index mapping
Utilize neural word embeddings in NLP applications
Build and evaluate text recommender systems using TF-IDF

Mastering NLP from Foundations to LLMs

Course Duration - 5 hrs 40 min

This ebook covers mathematical foundations & advanced techniques for NLP, machine learning, and LLMs. It provides complete NLP system design in Python code and includes expert opinions on future trends to help you solve real-world business problems.

Course Objectives:

Describe the mathematical foundations of machine learning and NLP
Implement advanced techniques for preprocessing text data and analysis
Design ML-NLP systems in Python
Model and classify text using traditional machine learning and deep learning methods
Explain the theory and design of LLMs and their implementation for various applications in AI
Describe NLP insights, trends, and expert opinions on its future direction and potential

The Handbook of NLP with Gensim

Course Duration - 5h 10 min

Computers cannot understand texts or organize documents. Texts must first be converted into numeric values before they can be used to unlock the hidden connection between documents into topics. This easy-to-follow ebook simplifies these processes for you, unveiling the power of Gensim to perform complex topic modeling, and showcases professional use cases in medical, legal, and other business operations.

Course Objectives:

Convert text into numerical values such as bag-of-word, TF-IDF, and word embedding
Use various NLP techniques with Gensim, including Word2Vec, Doc2Vec, LSA, FastText, LDA, and Ensemble LDA
Build topical modeling pipelines and visualize the results of topic models
Implement text summarization for legal, clinical, or other documents
Apply core NLP techniques in healthcare, finance, and e-commerce
Create efficient chatbots by harnessing Gensim's NLP capabilities

Natural Language Processing with Flair

Course Duration - 3 hrs 20 min

Natural Language Processing with Flair is a ebook for NLP developers, data scientists, and machine learning enthusiasts who want to get up to speed with Flair to be able to put their knowledge to work by solving real-life problems. The ebook features a number of hands-on exercises showing how to create and deploy Flair NLP solutions with ease.

Course Objectives:

Describe core NLP terminology and concepts
Identify the capabilities of the Flair NLP framework
Use Flair s state-of-the-art pre-built models
Build custom sequence labeling models, embeddings, and classifiers
Identify a novel text classification technique called TARS
Determine how to build applications with Flair and how to deploy them to production

Mastering Transformers

Course Duration - 7 hrs 42 min

Transformer-based language models have dominated natural language processing studies and become a new paradigm. With this NLP transformers ebook, you'll be able to implement multimodal solutions, including text-to-image (Stable Diffusion).

Course Objectives:

Solve simple-to-complex NLP problems with Python
Determine how to solve classification/regression problems with traditional NLP approaches
Train a language model and explore how to fine-tune models to the downstream tasks
Explain how to use transformers for generative AI and computer vision tasks
Build transformer-based NLP apps with the Python transformers library
Focus on language generation such as machine translation and conversational AI in any language
Speed up transformer model inference to reduce latency

Applied Generative AI and Natural Language Processing with Python

Course Duration - 9 hrs 20 min

Dive into the world of generative AI and natural language processing with Python. This course covers the fundamentals and advanced techniques, including transformers, Huggingface, and prompt engineering. Gain practical experience in building, fine-tuning, and deploying AI models for real-world applications.

Course Objectives:

Master tokenization and word embedding techniques for NLP
Build and fine-tune AI models using Huggingface and OpenAI APIs
Implement sentiment analysis and text summarization methods
Design effective prompts to optimize AI model performance
Utilize vector databases for enhanced data retrieval efficiency
Apply advanced RAG techniques to integrate external data sources

Essential Career Skills Pack

Productivity and Time Management

Course Duration - 30 min

It seems that there is never enough time in the day. But, since we all get the same 24 hours, why is it that some people achieve so much more with their time than others? This course will explain how to plan and prioritize tasks, so that we can make the most of the limited time we have. By using the time-management techniques in this course, you can improve your ability to function more effectively – even when time is tight and pressures are high. So, by the end of the course you will have the knowledge, skills and confidence to be an effective manager of your time.

Course Objectives:

Set your priorities to better manage your time
Improve your productivity by sharpening your focus and multitasking effectively

Detailed Course Outline:

Productiity & Time Management
Prioritization
Getting Things Done

Procrastination
Multitasking & Focus
Summary

Basic Digital Skills

Course Duration - 13 min

With the rise of digital transformation and technology, having a basic digital literacy is essential for all types of jobs, regardless of the industry. To stay competitive and be successful in the workplace, enhancing your digital skills should be a top priority.

Course Objectives:

Recall the essential digital skills framework
Elaborate on the toolkit of essential digital skills
Identify how to develop or improve your digital skills

Detailed Course Outline:

The Essential Digital Skills Framework
The Toolkit of Essential Digital Skills

Developing Digital Skills
Summary

4 Ways to Boost Creativity

Course Duration - 30 min

The digital economy is opening up ways for everyone to be creative. It doesn’t just mean being artistic – it’s more about ideas, solutions, alternatives, incremental improvements. Peter Quarry and Eve Ash discuss ways that mental capacity can be developed, perspectives changed, group power leveraged and making things actually happen.

Course Objectives:

Define creativity
Think outside the box
Develop the right mental attitude
Leverage the power of groups
Ensure managers make it happen

Detailed Course Outline:

What is Creativity at Work?
Learn to Think Outside the box
Develop the Right Mental Capacity

Laverage the Power of Groups
Ensure Managers Make It Happen
Summary

The 11 Essential Career Soft Skills

Course Duration - 1 hr 10 min

Soft Skills are the traits, characteristics, habits, and skills needed to survive and thrive in the modern work world. Soft skills aren't usually taught in school, but you will learn them all here in this course. Are you someone that other people in your organization and industry like to work with, collaborate with and partner with? Are you seen as a valuable asset to any new project that comes along?

This soft skills training course will teach you how to develop the skills that can make the difference between a lackluster career that tops out at middle management versus one that lands you in the executive suite. Or to wherever you define career success. So many soft skills seem like common sense at first glance, but they are not commonly applied by most workers. This soft skills training course will give you an edge over your competitors. It will also make your job, your career and your life more rewarding and enjoyable.

Course Objectives:

Understand how to be a great communicator
Become a stronger listene
Appear professional to co-workers and bosses of all ages
Avoid common career blunders that often end careers
Manage expectations for bosses and colleagues
Position yourself for promotions
Make technology your asset, even if you are afraid of technology
Avoid the Not My Job Syndrome
Develop EQ to Match Your IQ
Develop leadership qualities

Detailed Course Outline:

Introduction
The Soft Tech Savvy Way to Always Be Essential
Not My Job, And I Am Happy to Do It
You Can Become a Master Communicator
Feedback Video for The 11 Essential Career Soft Skills
Become a Leader Without the Title or Formal Authority

Your EQ Will Beat a Higher IQ
Building Your Winning Team
Make Every One of Your Seconds Count
Unleash Your Inner Anthony Robbins
Avoid Being Uncool
Clothes Can Still Make or Break Your Career
Conclusion The 11 Essential Career Soft Skills
Extra: Developing Your Career Secret Sauce

Related Generative AI & ChatGPT Information:

How Much Do AI Training Courses Cost?

Public instructor-led AI course prices start at $460 per student. Group training discounts are available.

Self-Paced AI eLearning courses cost $475 at the starting point per student. Group purchase discounts are available.

What Generative AI Skills Should I Learn?

A: If you are wondering what Generative AI skills are important to learn, we've written a Generative AI Skills and Learning Guide that maps out Generative AI skills that are key to master and which of our courses teaches each skill.

Read Our Generative AI Skills and Learning Guide

How Can I Learn Generative AI?

Learning Generative AI involves understanding the foundational concepts of artificial intelligence, machine learning, and deep learning, followed by hands-on practice with relevant tools and frameworks.

Certstaffix Training offers three efficient methods to pursue your Generative AI training: Engaging Live Online Classes, Tailored Onsite Corporate Training for teams and Self-Paced eLearning.

View our Generative AI courses and available training methods.

Is It Hard to Learn Generative AI?

Learning Generative AI can vary in difficulty depending on your background and prior knowledge of related concepts.

For individuals with experience in computer science, programming, or machine learning, the process may be more straightforward as it builds upon foundational principles in these areas. For beginners, there can be a steeper learning curve since understanding Generative AI requires grasping concepts like neural networks, data preprocessing, and algorithm training.

However, with the right resources, such as Certstaffix structured courses, hands-on practice, and guidance from experienced instructors, anyone can gradually develop a strong understanding of Generative AI. Like any skill, persistence and consistent practice are key to mastering it.

Does Generative AI Require Coding?

The need for coding in Generative AI largely depends on the tools and platforms being used, as well as the user's goals. Modern Generative AI platforms, such as ChatGPT or DALL·E, often provide user-friendly interfaces that require little to no coding knowledge. These tools enable users to generate content, images, or text through simple commands or prompts.

However, for those looking to customize or build their own Generative AI models, coding is typically required. This may involve knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch. Understanding coding can also help in fine-tuning models, integrating AI into larger systems, or creating uniquely tailored applications.

Bottom line, while coding can enhance the scope of possibilities, it is not usually necessary for leveraging Generative AI's capabilities as an end user.

Can Anybody Learn AI?

Absolutely, anyone with interest and dedication can learn AI. While having a background in mathematics, programming, or data science can be advantageous, they are not strict prerequisites. Numerous online courses, tutorials, and resources are available to cater to learners of all levels, from beginners to advanced practitioners. The key lies in starting with fundamental concepts, such as understanding algorithms and machine learning basics, and gradually advancing to more complex topics. With consistent effort, anyone can develop the skills required to explore and contribute to the exciting field of AI.

Is it Worth Doing an AI Course?

Deciding whether to pursue an AI course ultimately depends on your goals, interests, and career aspirations. AI is one of the fastest-growing fields, with applications spanning industries such as healthcare, finance, entertainment, and more. Taking a course can be a valuable investment, equipping you with the knowledge and skills to tap into these opportunities. Furthermore, structured courses often provide hands-on projects, mentorship, and certifications that can enhance your resume and increase your credibility in the job market.

However, it’s important to assess the quality of the course and its relevance to your objectives. A well-structured AI course should provide a balance of theoretical knowledge, like understanding algorithms or neural networks, and practical experience with tools such as TensorFlow or PyTorch. Whether you aim to transition into a career in AI, enhance your current role, or simply satiate your curiosity, an AI course can offer significant value when aligned with your ambitions and commitment to learning.

How Is AI Used in Excel?

A: Many of Excel's features and functions are powered by artificial intelligence (AI) or have AI-like capabilities. These tools work to process large amounts of data for users, streamline workflows, and increase accuracy. Some of the best applications of AI in Excel include data analysis, data visualization, and formula generation, but it can also supercharge basic functions. Copilot allows users to harness the power of AI through prompts to provide relevant suggestions and shortcuts. Additionally, ChatGPT can be integrated with the program through the use of an add-on or used in tandem with Excel.

More Information on How Excel Integrates With AI

Where Can I Learn More About AI?

AI Blogs

AI Groups

AI Online Forums

Explore AI Classes Near Me:

Certstaffix Training provides AI classes near me or online, depending on the number of students involved. We offer online courses for individual learners, as well as in person classes at your office for corporate groups. Our trainers are highly experienced professionals with the expertise necessary to help you gain a thorough understanding of AI concepts and tools. With our courses available online for individuals or in person for corporate groups, it's easy to develop your AI skills. Start learning today and see how Certstaffix Training can help you reach your goals.

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