45 Hrs
3702+ Enrollments
Deep Learning with Python Training
The Deep Learning with Python Training course is an in-depth program that provides hands-on experience with popular Deep Learning libraries, such as TensorFlow and Keras. The course is taught by industry experts who will guide you through every step of the process, from basic concepts to advanced techniques. By the end of the course, you will be able to build and deploy your own deep learning models for various real-world applications.
Deep Learning with Python Training
Overview of Course
The Deep Learning with Python Training course is designed for learners who want to master the fundamentals of Deep Learning and gain expertise in building deep neural networks using Python. The course covers various deep learning concepts, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders.
Course Highlights
Hands-on experience with popular deep learning libraries like TensorFlow and Keras
Real-world applications of deep learning
Expert-led training with industry professionals<br /><br />
Key Differentiators
Personalized Learning with Custom Curriculum
Training curriculum to meet the unique needs of each individual
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Flexible Schedule & Delivery
Choose between virtual/offline with Weekend options
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World Class Learning Infrastructure
Our learning platform provides leading virtual training labs & instances
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Real-world Projects
We work with experts to curate real business scenarios as training projects
Skills You’ll Learn
Understand the fundamentals of deep learning
Build and deploy deep neural networks using TensorFlow and Keras
Develop applications such as image and speech recognition, natural language processing, and recommendation systems
Analyze and optimize deep learning models
Gain expertise in various deep learning techniques
Training Options
1-on-1 Training
Access to live online classes- Flexible schedule including weekends
- Hands-on exercises with virtual labs
- Session recordings and learning courseware included
- 24X7 learner support and assistance
- Book a free demo before you commit!
Corporate Training
- Everything in 1-on-1 Training plus
- Custom Curriculum
- Extended access to virtual labs
- Detailed reporting of every candidate
- Projects and assessments
- Consulting Support
- Training aligned to business outcomes
Unlock Organizational Success through Effective Corporate Training: Enhance Employee Skills and Adaptability- Choose customized training to address specific business challenges and goals, which leads to better outcomes and success.
- Keep employees up-to-date with changing industry trends and advancements.
- Adapt to new technologies & processes and increase efficiency and profitability.
- Improve employee morale, job satisfaction, and retention rates.
- Reduce employee turnovers and associated costs, such as recruitment and onboarding expenses.
- Obtain long-term organizational growth and success.
Course Reviews
Curriculum
- Tensorflow
- Keras
- ANN Intuition
- The Neuron
- The Activation Function
- How do Neural Networks work?
- How do Neural Networks learn?
- Gradient Descent
- Stochastic Gradient Descent
- Back propagation
- Building an ANN
- Installing Keras
- Evaluating the ANN
- Improving the ANN
- Tuning the ANN
- Matplotlib
- Pillow
- OpenCV
- CNN Intuition
- What You'll Need for CNN
- What are convolutional neural networks?
- Step 1(a) - Convolution Operation
- Step 1(b) - ReLU Layer
- Step 2 - Pooling
- Step 3 - Flattening
- Step 4 - Full Connection
- Softmax & Cross-Entropy
- Building a CNN
- Evaluating CNN
- Improving CNN
- Tuning the CNN
- RNN Intuition
- The idea behind Recurrent Neural Networks
- The Vanishing Gradient Problem
- LSTMs
- Practical intuition
- EXTRA: LSTM Variations
- Building a RNN
- Evaluating RNN
- Improving RNN
- Tuning RNN
- SOMs Intuition
- How do Self-Organizing Maps Work?
- Why revisit K-Means?
- K-Means Clustering (Refresher)
- How do Self-Organizing Maps Learn?
- Reading an Advanced SOM?
- Tokenization
- Stemming
- Lemmatization
- POS TagName
- Entity Recognition
Meet the instructor and learn about the course content and teaching style.- Make informed decisions about whether to enroll in the course or not.
- Get a perspective with a glimpse of what the learning process entails.
Description
Target Audience:
- Software developers
- Data scientists
- Machine learning engineers
- Anyone interested in deep learning
Prerequisites:
- Basic programming knowledge in Python
- Understanding of linear algebra and calculus
- Familiarity with machine learning concepts
Benefits of the course:
- Master the fundamentals of deep learning
- Hands-on experience with popular deep learning libraries
- Learn to develop applications for real-world problems
- Expert-led training with industry professionals
- Flexible learning options
Exam details to pass the course:
- There is no exam to pass the course.
- The course is designed to provide hands-on experience and practical knowledge in deep learning concepts.
Certification path:
- After completing the Deep Learning with Python Training course, you will receive a certificate of completion from Skillzcafe.
- There are no additional certifications required to learn this course.
Career options after doing the course:
- Machine learning engineer
- Data scientist
- Deep learning researcher
- AI developer
- Computer vision engineer
Why should you take this course from Skillzcafe:
Expert-led training with industry professionals- Hands-on experience with popular deep learning libraries
- Flexible learning options
- Certificate of completion from Skillzcafe
- Lifetime access to course materials
FAQs
The Deep Learning with Python Training course is a 45-hour program.
No, prior experience in deep learning is not required, but basic knowledge of programming and machine learning concepts is recommended.
The course is taught using Python, which is one of the most popular programming languages for deep learning.
Yes, once you complete the course, you will have lifetime access to the course materials, including videos, exercises, and projects.
You will work on various real-world projects, such as image and speech recognition, natural language processing, and recommendation systems, to apply the concepts you learn in the course.
You will need a computer with internet access and a Python environment set up with TensorFlow and Keras installed. The course instructors will provide guidance on setting up the required software.
Skillzcafe has a 7-day money-back guarantee. If you are not satisfied with the course, you can request a full refund within 7 days of the course start date.
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