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IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
- Introduction to TensorFlow
- Computational Graph
- Stochastic Gradient Descent
- Visual TensorBoard
- Keras with TensorFlow
- Role of Activation functions in ANN network
- Activation Functions:
- Sigmoid (Binary)
- Softmax (Multiclass)
- ReLU (Linear)
- Introduction to ANN
- Concept of Perceptron
- Perceptron Training Rule
- Gradient Descent Rule
- Gradient Descent
- Stochastic Gradient Descent
- Backpropagation
- Some problems in ANN
- Overfitting and Capacity
- Cross Validation
- Feature Selection
- Regularization
- Hyperparameters
- Introduction to CNNs
- Principles behind CNNs
- Kernel and Multiple Filters
- CNN Image Classification demo
- Introduction to RNNs
- Unfolded RNNs
- Seq2Seq RNNs
- LSTM
- RNN applications
- Image Processing
- Natural Language Processing
- Speech Recognition
- Video Analytics
- Image Classification with CNN - Keras
- Natural Language Processing with NKTL live project
Deep Learning with Python courses will get you ready for an AI career. Deep Learning is also one of the highly coveted skills in the tech industry. This course covers popular Deep Learning algorithms: Convolutional Networks, BatchNorm, RNNs, etc., with the case studies from autonomous driving, healthcare, Natural language processing, etc., With this course, you will not only master the concept behind deep learning but also see the application of the real world.
Deep Learning is a subset of machine learning that utilizes artificial neural networks to simulate the human brain's learning process. It involves training deep neural networks with multiple layers to extract intricate patterns and make accurate predictions or classifications.
Deep Learning works by building and training neural networks with multiple layers of interconnected nodes called neurons. Each layer extracts and transforms data, passing it to the next layer for further processing. Through a process known as backpropagation, the network adjusts the weights of its connections to minimize errors and improve its predictions.
Deep Learning has numerous applications across various industries. It is used in image and speech recognition, natural language processing, autonomous vehicles, healthcare diagnostics, recommendation systems, fraud detection, and many more.
Popular Deep Learning frameworks include TensorFlow, PyTorch, Keras, Caffe, and Theano. These frameworks provide efficient tools and libraries for building, training, and deploying deep neural networks.
Deep Learning is a subset of Machine Learning that focuses on training deep neural networks with multiple layers. While traditional Machine Learning algorithms require manual feature extraction, Deep Learning models automatically learn hierarchical representations from raw data, reducing the need for manual feature engineering.
Deep learning offers a wide range of job roles in deep learning. Some popular roles include deep learning engineer, data scientist, research scientist, machine learning engineer, computer vision engineer, and natural language processing engineer. These roles can be found in industries such as healthcare, finance, e-commerce, autonomous vehicles, and more.
To excel in a deep learning career, you should have a strong foundation in mathematics, particularly linear algebra and calculus. Proficiency in programming languages like Python and experience with deep learning frameworks such as TensorFlow or PyTorch are essential. Additionally, skills in data preprocessing, model optimization, and problem-solving are highly valuable in the field.
Salaries for deep learning professionals vary depending on factors like experience, location, and industry. On average, deep learning engineers and data scientists earn competitive salaries. According to industry reports from Indeed, in the United States, the median salary for a deep learning engineer is INR $165,574 per year, with senior-level professionals earning even higher.
Networking and professional connections can greatly benefit deep learning careers. Building connections with fellow professionals, researchers, and industry experts can lead to collaborations, mentorship opportunities, and access to job openings. Networking platforms, industry events, and online communities dedicated to deep learning provide avenues to connect with
Continuous learning is critical in deep learning careers due to the rapid advancements and evolving nature of the field. To stay relevant and competitive, professionals need to stay updated with the latest research papers, attend conferences and workshops, and explore new techniques and tools. Investing in continuous learning ensures that you are equipped to tackle new challenges and seize emerging opportunities.
The future of deep learning is promising, as it continues to advance and find applications in various industries. With ongoing research and development, deep learning models are expected to become more efficient, interpretable, and capable of handling complex tasks. As data continues to grow exponentially, deep learning's ability to extract valuable insights from large datasets will be increasingly valuable, driving further innovation and adoption in the coming years.
DataMites™ provide flexible learning options from traditional classroom training, lastest virtual live classroom to distance course. Based on your location preference, you may have one or more learning options
This course is perfectly aligned to the current industry requirements and gives exposure to all latest techniques and tools. The course curriculum is designed by specialists in this field and monitored improved by industry practitioners on continual basis.
All certificates can be validated with your unique certification number at IABAC.org portal. You also get candidate login at exam.iabac.org , where can find your test results and other relevant validation details.
The results of the Exam are immediate, if you take online test at exam.iabac.org portal. The certificate issuance, as per IABAC™ terms, takes about 7-10 bussiness days for e-certificate.
No, the exam fees are already included in the course fee and you will not be charged extra.
Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constrains, your relation manager at DataMites™ shall assist you with part payment agreements
DataMites™ has a dedicated Placement Assistance Team(PAT), who work with candidates on individual basis in assisting for right Data Science job.
You get 100% refund training fee if you the training is not to your satisfaction but the exam fee will not be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis
DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with latest information on Data Science as well as job updates.
DataMites is widely recognized as one of the best deep learning course providers. With their comprehensive curriculum, renowned faculty, and industry-recognized certifications, DataMites stands out as a global institute for deep learning education. Their courses offer a blend of theoretical concepts and hands-on projects, ensuring a thorough understanding of deep learning algorithms and their real-world applications. Additionally, DataMites provides flexible learning options, internship opportunities, and dedicated placement assistance, making them the preferred choice for individuals seeking to build a successful career in deep learning.
DataMites offers the following Deep Learning Certification Training:
The Deep Learning Course has a duration of 4 to 6 months, with a total of 200 hours of training. Training sessions are conducted on weekdays and weekends, providing flexibility to choose based on your availability.
The DataMites Certified Deep Learning Expert Course is a comprehensive program that focuses on providing in-depth knowledge and practical skills in the field of deep learning. Participants will learn various deep learning algorithms, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). The course covers topics like natural language processing, computer vision, and deep reinforcement learning, enabling participants to understand and implement advanced deep learning techniques.
The DataMites Certified Computer Vision Expert Course is designed to provide individuals with expertise in computer vision, a subfield of deep learning. Participants learn to apply deep learning algorithms and techniques to tasks such as image classification, object detection, image segmentation, and facial recognition. The course covers popular computer vision frameworks and tools, enabling students to develop real-world computer vision applications.
The DataMites Deep Learning with Python Courses are designed to help participants learn the fundamentals of deep learning using Python programming language. The courses cover essential topics such as neural networks, activation functions, backpropagation, and gradient descent. Participants will also explore popular deep learning frameworks like TensorFlow and Keras, gaining hands-on experience in building and training deep learning models for various applications.
The DataMites Deep Learning TensorFlow Course focuses specifically on deep learning with TensorFlow, a popular deep learning framework. This course provides in-depth training on building and deploying deep learning models using TensorFlow. Participants learn to implement various deep learning architectures, optimize models, and leverage TensorFlow's features for efficient deep learning development. The course prepares individuals to become proficient in deep learning using the TensorFlow framework.
There are compelling reasons to choose DataMites for Online Deep Learning Training:
The fee for Deep Learning training at DataMites varies based on the chosen course and training mode. Below is the fee range for different regions:
The Flexi-Pass option allows you to attend DataMites training sessions for a duration of 3 months. It provides added support and guidance, allowing you to clear doubts and review concepts effectively.
Yes, upon completing the Deep Learning Training, you will be awarded the prestigious IABAC® certification. This certification holds global recognition and adds value to your professional profile.
In case you miss a training session, you can schedule a makeup class with your instructors at your convenience. For Online Deep Learning Training, all sessions are recorded and uploaded, enabling you to catch up on missed content at your own pace.
The DataMites Placement Assistance Team (PAT) offers comprehensive support, including:
Certainly! You have the option to request help sessions to clarify doubts or gain a better understanding of specific topics covered in the training.
DataMites accepts various payment methods, including cash, net banking, checks, debit cards, credit cards, PayPal, Visa, Mastercard, and American Express.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.
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