Deep Learning Specialty Training

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Instructor-Led Training Parameters

Course Highlights

  • Instructor-led Online Training
  • Project Based Learning
  • Certified & Experienced Trainers
  • Course Completion Certificate
  • Lifetime e-Learning Access
  • 24x7 After Training Support

Deep Learning Specialty Training Course Overview

Unlock the power of Artificial Intelligence with Multisoft Systems' Deep Learning Specialty certification course. This immersive training program delves into the core concepts and cutting-edge techniques of Deep Learning, enabling students to build, train, and implement advanced neural networks. Shape your career and drive digital transformation with our comprehensive course. Explore. Learn. Innovate. Your journey into the AI frontier begins here!

The Deep Learning Specialty Certification Course by Multisoft Systems is an intensive training program designed to equip learners with the theoretical knowledge and practical skills required to excel in the field of deep learning. This course explores the advanced concepts of artificial intelligence, focusing predominantly on the methodology and application of deep learning algorithms. The curriculum covers fundamental topics like neural networks, back propagation, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Students will also delve into more complex subjects like generative adversarial networks (GANs), reinforcement learning, and the ethics of AI. Through hands-on exercises and projects, students gain practical experience implementing deep learning models using popular libraries and frameworks like TensorFlow and PyTorch. The course culminates in a capstone project, allowing learners to showcase their newly acquired skills in a real-world context.

Overall, Multisoft's Deep Learning Specialty Certification Course offers a comprehensive, in-depth understanding of deep learning concepts, bridging the gap between academic theory and industry practice. Whether you're an aspiring data scientist, AI specialist, or just an enthusiast, this course is designed to help you stay at the forefront of this evolving field.

Deep Learning Specialty Course Objective
  • Gain a comprehensive understanding of various deep learning models, including Neural Networks, Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN).
  • Learn to implement deep learning algorithms, understand neural networks, and traverse layers of data abstraction to understand the architecture of different types of deep networks.
  • Develop a solid understanding of Back propagation - a fundamental concept in deep learning used for training neural networks.
  • Learn to build, train, and deploy various types of deep architectures including CNNs, RNNs, auto encoders, and Generative Adversarial Networks (GANs).
  • Understand the role of different activation functions, loss functions, optimization algorithms, regularization methods, and understand how to choose the appropriate function or method for a given task.
  • Learn how to use GPUs for training deep learning models more efficiently. Understand the ethical considerations, privacy issues, and societal implications of using deep learning technologies.
Deep Learning Specialty Online Training
  • Recorded Videos After Training
  • Digital Learning Material
  • Course Completion Certificate
  • 24x7 After Training Support
Target Audience
  • Machine Learning Engineers and Data Scientists seeking to enhance their knowledge of deep learning and apply it in their professional field.
  • Software Engineers wanting to understand and apply deep learning models in creating or enhancing applications.
  • Research Scholars and Academicians who are researching or teaching in fields where deep learning models could be applied.
  • Professionals from other disciplines who are keen on switching their careers into AI and Machine Learning.
  • Students studying computer science or related fields who wish to gain expertise in deep learning.
  • Tech enthusiasts and hobbyists who have a keen interest in AI, machine learning, and deep learning technologies.
Deep Learning Specialty Course Prerequisites
  • Strong foundation in mathematics: Proficiency in linear algebra, calculus, probability, and statistics is essential for understanding deep learning concepts and algorithms. Programming skills: Proficiency in at least one programming language, preferably Python, which is the most used language in the deep learning community.
  • Basic understanding of machine learning: Familiarity with key machine learning concepts, algorithms, and techniques, such as supervised and unsupervised learning, feature engineering, and model evaluation.
  • Knowledge of neural networks: Understanding the basic concepts and architecture of neural networks, including feedforward networks, backpropagation, and gradient descent.
  • Familiarity with deep learning frameworks: Experience with popular deep learning libraries and frameworks, such as TensorFlow, Keras, or PyTorch, is highly beneficial.
  • Hands-on experience: Practical experience applying deep learning models to real-world problems, such as image classification, natural language processing, or reinforcement learning.
Deep Learning Specialty Course Certification
  • Multisoft Systems provides a globally recognized training certificate after successful completion of Deep Learning Specialty certification course.

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Deep Learning Specialty Training Course Content

Module 1: Introduction to Deep Learning

  • Introduction to deep learning trends and applications
  • Examples of deep learning applications

Module 2: Neural Network Basics

  • Machine learning problem setup and neural network mindset
  • Vectorization for efficient computation

Module 3: Shallow Neural Network

  • Building a neural network with one hidden layer
  • Understanding forward propagation and backpropagation

Module 4: Deep Neural Network

  • Computation in deep learning
  • Building and training deep neural networks for computer vision tasks

Module 5: Practical Aspects of Deep Learning

  • Initialization methods for deep neural networks
  • Regularization techniques to prevent overfitting

Module 6: Optimization Algorithms

  • Advanced optimization techniques for neural networks
  • Random minibatching and learning rate decay

Module 7: Hyperparameter Tuning, Batch Normalization, Frameworks

  • Introduction to the TensorFlow framework
  • Training neural networks on TensorFlow datasets

Module 8: ML Strategy

  • Strategic guidelines for setting goals and managing ML production workflow
  • Error analysis procedures

Module 9: Foundations of Convolutional Neural Networks

  • Understanding pooling and convolutional layers
  • Building deep CNNs for image classification

Module 10: Deep Convolutional Models: Case Studies

  • Exploring advanced tricks and methods in deep CNNs
  • Applying transfer learning to pretrained models

Module 11: Object Detection

  • Using CNNs for object detection tasks

Module 12: Face Recognition & Neural Style Transfer

  • Applying CNNs for face recognition tasks
  • Implementing neural style transfer for art generation

Module 13: Recurrent Neural Networks

  • Introduction to recurrent neural networks (RNNs)
  • Variants of RNNs for sequential data modeling

Module 14: Natural Language Processing & Word Embeddings

  • NLP applications with deep learning models
  • Word embeddings for text analysis

Module 15: Sequence Models & Attention Mechanism

  • Enhancing sequence models with attention mechanisms
  • Speech recognition and audio data processing

Module 16: Transformer Network

  • Understanding the functioning of transformer networks


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Deep Learning Specialty Training (MCQ) Assessment

This assessment tests understanding of course content through MCQ and short answers, analytical thinking, problem-solving abilities, and effective communication of ideas. Some Multisoft Assessment Features :

  • User-friendly interface for easy navigation
  • Secure login and authentication measures to protect data
  • Automated scoring and grading to save time
  • Time limits and countdown timers to manage duration.
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Deep Learning Specialty Corporate Training

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Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements


Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

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Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

Learning Assessment

Be it schedule, duration or course material, you can entirely customize the trainings depending on the learning requirements

Certification Training Achievements: Recognizing Professional Expertise

Multisoft Systems is the “one-top learning platform” for everyone. Get trained with certified industry experts and receive a globally-recognized training certificate. Some Multisoft Training Certificate Features :

  • Globally recognized certificate
  • Course ID & Course Name
  • Certificate with Date of Issuance
  • Name and Digital Signature of the Awardee
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