Fremont, CA – July 2025 – Big Data Trunk, a leader in cutting-edge data and AI education, is proud to announce its latest addition to the Byte-Sized Deep Learning Series: "Handling Text Data with Keras" — a hands-on, 90-minute virtual training designed to empower learners with the skills needed to manage and model text data using modern deep learning frameworks.

As part of its mission to deliver continuous improvement and innovative learning opportunities to clients and the wider tech community, Big Data Trunk’s new offering focuses on one of the most critical aspects of machine learning: Natural Language Processing (NLP). This course is specially tailored for aspiring machine learning engineers and data scientists looking to gain a deeper understanding of how to prepare and process textual data — a core competency in today's AI-driven world.

Unlock the Power of Language with Deep Learning
In the world of AI, teaching machines to understand human language is no small feat. Unlike numerical or image data, text data is unstructured, variable in length, and steeped in semantics. Big Data Trunk’s new course titled "Byte-Sized Deep Learning Series: Handling Text Data with Keras" addresses these challenges head-on, offering learners practical tools and techniques to bridge the gap between raw text and powerful machine learning models.

This 90-minute session will guide participants through the entire preprocessing pipeline—from tokenization and padding to vocabulary creation and embedding. The session will also introduce learners to Keras’s powerful TextVectorization layer, a flexible and intuitive tool for turning raw text into model-ready input.

What You’ll Learn
By the end of this bite-sized training, learners will walk away with real, actionable skills they can apply to their next NLP project. Key learning objectives include:

· Understanding the unique challenges of working with text data in machine learning and deep learning environments.

· Applying key text preprocessing steps such as tokenization, padding, and vocabulary building.

· Leveraging embedding layers and word embeddings to represent textual information numerically.

· Utilizing the Keras TextVectorization layer to streamline text preprocessing within neural networks.

Participants will also gain practical experience with Python and TensorFlow as they build a basic sentiment analysis model, learning how to extract meaning from text using deep learning.

Who Should Attend?
This course is built for:

· Students and professionals in the field of machine learning who understand the basics of model-building and are ready to branch out into natural language processing.

· Developers who have a working knowledge of Python, Keras, and TensorFlow (particularly the Sequential model and common layer types).

· Anyone eager to build their first text classification model using hands-on, guided labs.

Whether you're aiming to break into NLP or want to reinforce your existing skills, this course is a perfect gateway into text-based machine learning.

Interactive and Hands-On Learning Experience
To ensure maximum engagement and retention, this session features live hands-on labs using Jupyter Notebook or Google Colaboratory — giving participants flexibility and ease of use. Installation instructions for Python libraries and tools are provided, making it simple to get up and running.

Training materials are included in digital format, and real-time guidance ensures that learners can follow along and ask questions as they build their own neural networks.

Course at a Glance:
· Course Title: Byte-Sized Deep Learning Series: Handling Text Data with Keras

· Course Code: BDT495

· Duration: 90 minutes

· Format: Virtual (with hands-on labs)

· Materials: Provided (digital format)

· Tools Required: Jupyter Notebook or Google Colab

Course Curriculum Snapshot:
1. The Challenge with Text Data in ML/DL

· Why text is difficult to model

· Converting text into numeric tensors

2. Text Preprocessing

· Tokenization: Breaking down text into tokens

· Vocabulary Building: Mapping tokens to integers

· Padding: Making sequences uniform in length

· Hands-on demo with Tokenizer and pad_sequences

3. Embedding Layers & Word Embeddings

· Understanding the importance of embeddings

· Applying Keras’s Embedding layer

· Exploring output shapes in a dummy model

4. The Keras TextVectorization Layer

· What it is and how it works

· Automating tokenization, vocabulary, and padding

· Using TextVectorization in your own neural network

Join the Deep Learning Movement with Big Data Trunk
As the demand for AI and machine learning expertise continues to grow, Big Data Trunk is committed to offering accessible, targeted, and practical training to empower professionals and organizations alike. The Byte-Sized Deep Learning Series was developed to make high-impact learning achievable in short, focused sessions — ideal for busy professionals.

“We’ve designed this course for real-world application. It’s short, it’s hands-on, and it delivers immediate value,” says a Big Data Trunk instructor. “Whether you’re looking to build your first NLP model or sharpen your deep learning toolkit, this course provides a clear and guided path.”

Get Started Today
Ready to enhance your AI skillset? Book a call, sign up for the session, or contact us to learn more:

Big Data Trunk
39111 Paseo Padre Parkway, Suite #305
Fremont, CA 94538

Email: [email protected]
Call: +1-415-484-6702
Book a Call: calendly.com/bigdatatrunk
Website: https://bigdatatrunk.com

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About Big Data Trunk
Big Data Trunk is a global leader in data science, cloud, and AI education. With a mission to democratize learning and empower professionals with in-demand tech skills, the company offers a wide range of training programs for individuals, teams, and enterprises. Backed by industry experts and practical experience, Big Data Trunk delivers training that goes beyond theory — with real-world application at its core.