Mastering Deep Learning: An Intensive Boot Camp

Join our Mastering Deep Learning Boot Camp to gain practical expertise in neural networks and data analysis, designed for IT professionals eager to apply advanced AI techniques in real-world scenarios.

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Essential Skills Gained

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Master foundational deep learning concepts and mathematics.

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Utilize Anaconda and Jupyter Notebook expertly.

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Develop and deploy neural networks with Python and TensorFlow.

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Optimize and fine-tune deep learning models for peak performance.

Format

  • Instructor-led
  • 2 days with lectures and hands-on labs.

Audience

  • Experienced data analysts
  • Tech-savvy product managers
  • Advanced software developers
  • Team leads in tech fields

Description

Embark on a practical journey in our two-day Mastering Deep Learning Boot Camp, where you'll harness the power of deep learning—a sophisticated subset of machine learning that uses artificial neural networks to mimic human thought processes. This immersive course provides extensive coverage of key topics, including proficiency in TensorFlow and Keras, and offers 40% hands-on lab work to bridge theory with practice. Conclude the course empowered to build, train, and deploy solutions using deep learning principles leveraging Python.

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Upcoming Course Dates

September 15-16, 2025

10:00 AM - 6:00 PM

Virtual: Online - US/Eastern

Enroll

$2295

November 12-13, 2025

10:00 AM - 6:00 PM

Virtual: Online - US/Eastern

Enroll

$2295

Course Outline

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Introduction to Deep Learning

  1. Learn the impact of deep learning on business.

  2. Explore neurons, layers, weights, biases, and activation.

  3. Discover business applications of deep learning.

Setting up Deep Learning Environment

  1. Craft an effective environment for deep learning.

  2. Navigate Anaconda and Jupyter Notebook essentials.

  3. Lab: Establish a Python setup.

Introduction to TensorFlow and Keras

  1. Overview of TensorFlow and Keras functionality.

  2. Construct a neural network using Keras.

  3. Lab: Develop a basic neural network model.

Fundamentals of Neural Networks

  1. Define neural networks and their operations.

  2. Study forward and backward propagation.

  3. Lab: Apply a Multi-Layer Perceptron to a dataset.

Working with Data in Deep Learning

  1. Importance of data preprocessing in learning.

  2. Manage and prepare diverse data types.

  3. Lab: Process a dataset for learning tasks.

Tuning and Optimizing Deep Learning Models

  1. Utilize optimizers like SGD, Adam, RMSprop.

  2. Save and reload trained models effectively.

  3. Lab: Refine and enhance a neural network.

Deploying Deep Learning Models

  1. Understand model deployment processes.

  2. Implement model serving with TensorFlow Serving.

  3. Lab: Launch a trained model to production.

Real-world Applications of Deep Learning

  1. Investigate deep learning in various industries.

  2. Explore its use in healthcare, finance, and more.

Your Team has Unique Training Needs.

Your team deserves training as unique as they are.

Let us tailor the course to your needs at no extra cost.