AI & Deep Learning Course Training in Johor
- 24 Hours Classroom & Online Sessions
- 60+ Hours Assignments & eLearning
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- 2 Capstone Projects
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AI Training Overview in Johor
Gain both conceptual understanding and application-related skills in the three-day Certification Programme in AI and Deep Learning in Malaysia. Professionals with an aptitude for statistics and knowledge of programming languages such as Python, R and RStudio can launch their AI and Deep Learning career with this course. They will learn how to build AI applications, understand Neural Network architectures, create AI algorithms and minimise errors through advanced optimisation techniques.
Artificial Intelligence Course Outcomes
Artificial intelligence is a broad field that covers several disciplines that include speech recognition, chatbots, machine learning, deep learning, biometrics, text analysis, and processing. Artificial intelligence continues to make breakthrough advancements to improve our quality of life across an array of settings. Working in the space of artificial intelligence one requires an analytical bent of mind to run through technical information and solve problems using economical and effective methodological course of action. An AI specialist should know how to design, maintain, and translate highly technical and sensitive information in ways that can be understood by others. This AI Training in Malaysia introduces you to the concept of Artificial Intelligence and Deep learning and helps you in understanding Neural Network Architectures, structuring algorithms for new AI machines, and minimizing errors through advanced optimization techniques. This course provides a challenging avenue for exploring the basic principles, techniques, strengths, and limitations of the various applications of Artificial Intelligence. Students will also gain an understanding of the current scope, limitations, and societal implications of artificial intelligence globally. They will investigate the various AI structures and techniques used for problem-solving, inference, perception, knowledge representation, and learning. You will also learn to
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Who Should Sign Up?
- IT Engineers
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- Banking and Finance Analysts
- Marketing Managers
- Supply Chain Professionals
- HR Managers
- Math, Science and Commerce Graduates
AI & Deep Learning Training Modules
This Artificial Intelligence module has been conceived and structured to groom consummate AI professionals. This course will be the first stepping stone towards Artificial Intelligence and Deep Learning. In this module, you will be introduced to the analytics programming languages and will attempt to understand the evolution of AI and Deep Learning and learn the various applications and challenges faced in deep learning along with the best practices to overcome the challenges is also explained in detail. While there is a lot of statistical software and programming languages to perform deep learning activities, Python stands out from the rest. There are a lot of deep learning libraries such as Keras, TensorFlow, Theano, PyTorch, etc. and one will learn about Keras as well as TensorFlow as part of the training module.
Understand the evolution of AI and Deep Learning and learn the various applications of Deep Learning in building Artificial Intelligence applications. A brief history of Deep Learning and the pace of progress in the space of deep learning is pivotal for budding and emerging data scientists as well as AI experts. Challenges faced in deep learning along with the best practices to overcome the challenges is also explained in detail.
While there are a lot of statistical software and programming languages to perform deep learning activities, Python stands out from the rest. There are a lot of deep learning libraries such as Keras, TensorFlow, Theano, PyTorch, etc., and one will learn about Keras as well as TensorFlow as part of the training module. Image processing is an amazing field to become proficient at and hence you will also learn OpenCV, which stands for Open Computer Vision. The future belongs to Open-source libraries and the fastest development on emerging algorithms will happen in this space. Learning these concepts will help us gain an edge over competitors.
Understanding the treatment of both linearly separable boundaries as well as non-linear boundaries is pivotal for the success of AI experts as well as Data Scientists. In this module, one will learn about handling linear boundaries using the Perceptron algorithm. Understand how weights are assigned and how they are updated each time to reduce the error function. Learn about the Backpropagation algorithm and its application in reducing error using the Perceptron algorithm.
Artificial Neural Network, also called MLP or Multilayer Perceptron is used to handle nonlinear problems. Understand the various network architectures along with different layers including input layers, hidden layers, output layers, etc. Also learn about the various activation functions, error functions, optimization algorithms including Batch Gradient Descent, Stochastic Gradient Descent, Mini-batch SGD, etc.
Understand working with videos and images because the amount of data getting generated in this space is outstripping the volume of textual data. Understand the various features to be extracted from images including edges, textures, etc., by applying various kinds of filters such as Sobel, Harris Corner Detector. Also, learn about face detection using Viola-Jones and tracking human faces in videos. Alongside this also learn about a few image-related models such as image segmentation, image recognition, etc.
Understand how to work with images and videos for building predictive models. Learn about convolution layers as well as handling very small datasets. Understand how to improve the accuracy of models by performing data augmentation activities. Also one should be aware of the use of pre-trained models using feature extraction, fine-tuning, etc., in solving business problems. Finally visualizing the activation layers and heat maps for activation will complete the study to the fullest.
Understand working with textual sequence data and how to perform a one-hot encoding of words and characters. Learn about bi-directional RNNs as well as deep bi-directional RNNs. Learn about various RNN topologies and network architectures. Vanishing and exploding gradient problems are very prevalent in the field of recurrent neural networks. Understand Backpropagation Through Time, which is a different but slight variation from the regular backpropagation algorithm.
Advanced techniques in handling textual and sequential data are LSTMs and GRUs. Also, understand about forecasting temperature. Learn about bi-directional LSTMs and deep bi-directional LSTMs . Also, understand the stacking of various recurrent layers. Stacking recurrent layers will improve accuracy and understanding the same is extremely pivotal for the success of AI algorithms. Also, learn about 1D convolution for time series data. Finally combining CNN and RNN models is an art, which is explained in detail.
Learn about the renowned unsupervised deep learning algorithm called Autoencoders. Understand about generating sentences using a combination of LSTM and Autoencoders. Also, learn about variational autoencoders for generating images and editing images. Another most used algorithm in the family of neural network algorithms is GANs. Learn about systematically implementing GAN. Learn about various elements of GANs including Deep Convolutional Generative Adversarial Network. A brief introduction to WaveNet, which is used to produce audio is also explained.
Board games such as Tic-Tac, Go, AlphaGo uses reinforcement learning algorithms to build unbeatable games. Learn how Artificial Intelligence games are built using Neural network algorithms. Maximizing future rewards is the key to building reinforcement learning. Learn how to balance between exploration as well as exploitation in Q-Learning.
Artificial Intelligence Trends in Johor
AI study and research in Malaysia are getting amazing traction from all corners of the industry as well as the government of Malaysia. The demand for AI professionals has spawned the need for good AI training institutes. The AI training landscape in Malaysia is dotted with a plethora of courses. It is imperative to choose an institute where the faculty have practical experience in developing AI solutions for businesses and research.
360DigiTMG is one such institute that has specialized in emerging technologies like Artificial Intelligence, Machine Learning, Deep Learning, and Data Science. Our faculty spend 70% of their time on live projects and 30% on training. The course curriculum has been developed by industry experts. Students get exposure to live projects with INNODATATICS(US) as part of the course curriculum. In Malaysia, AI professionals command the highest pay packages and the best place to gear up for an AI career is with 360DigiTMG.
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Start your course at RM 1333.33
Full Course Fee RM 4000 (excl 6%SST)
0% Interest Free Installments options available.
How We Prepare You
Additional Assignments of over 60-80 hours
Live Free Webinars
Resume and LinkedIn Review Sessions
6 Months Access to LMS
Job Assistance in Artificial Intelligence Fields
Unlimited Mock Interview and Quiz Session
Hands-on Experience in a Live Project
Life Time Free Access to Industry Webinars
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