Certificate Course in
Best AI & Deep Learning Course Training in Singapore
- 24 Hours Classroom & Online Sessions
- 60+ Hours Assignments & eLearning
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Academic Partners & International Accreditations
"AI market in the Asia Pacific to grow from $6 billion in 2017 to $136 billion in 2025 with key Industries like Business Services, Healthcare, and Retail to adopt AI." - (Source). AI has made incredible advances in the past few years and we have seen AI move into exciting new applications from autonomous shopping carts to AI-generated music. Today AI is leveraged across many sectors that perform repetitive tasks or are involved in problem-solving like predicting a product that someone may want to buy or finding the optimum number of taxis that a city needs. This technology is being extensively used for medical diagnosis, speech commands on mobile phones, video games, keeping email inbox clear of spam, and so on. AI and robotics are among the top five skill sets in demand in Singapore and it plans to build up AI skills for the digital economy. Join us and get the best training in AI and Deep learning in Singapore and be a part of this exciting journey into innovation and discovery.
AI & Deep Learning
- Computer Skills.
- Basic Mathematical Knowledge.
- Basic Data Science Concepts.
Artificial Intelligence Course Program Overview
Learn AI concepts and practical applications in the Certification Programme in AI and Deep Learning. Get set for a career as an AI expert. Gain both conceptual understanding and application-related skills in the three-day Certification Programme in AI and Deep Learning in Singapore. 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 minimize errors through advanced optimization techniques. After this program, they will be able to apply Computer Vision and Convolution Neural Networks for image processing.
Artificial intelligence (AI) is concerned with building smart machines capable of performing tasks just like Humans. It is an interdisciplinary science with multiple approaches and is becoming a dominant problem-solving technique in research labs and production industries. With data growing at an exponential rate and becoming more meaningful and contextually relevant is paving way for artificial intelligence and deep learning that is turning data into knowledge, conclusions, and actions.
What is Deep Learning?
Deep learning is a subset of Machine Learning in artificial intelligence where artificial neural networks find patterns in raw data by combining multiple layers of artificial neurons and as the layers increase so does the neural network’s ability to learn abstract concepts so much so that it can learn how to recognize human faces by passing knowledge from one layer to another.
AI Course Learning Outcomes in Singapore
This course is one of the best in Singapore that covers all aspects including the concepts, strategies, principles, and algorithms of AI along with its applications and use cases that will help students understand how AI is transforming lives around us. Artificial Intelligence is shaping up to be one of the biggest technological revolution the world has ever seen which is diffusing innovation throughout society and is contributing to driving business growth and production. AI is efficient in augmenting natural human expertise and has been successful in taking automation to new places. The main purpose of this course is to provide fundamental knowledge about AI and Deep Learning. Gain experience in how to Process and analyze unstructured data such as images, videos, and text. Students will explore how AI is used for problem-solving, reasoning, planning, natural language understanding, computer vision, automatic programming, machine learning, and so on. You will gain in-depth knowledge of algorithms of advanced AI which include statistical learning, reinforcement learning, deep learning, and natural language processing through research-oriented studies involving software programming. Students will also learn about deep learning concepts and models using Keras and TensorFlow frameworks and implement deep learning algorithms. You will also learn how to:
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Who Should Sign Up?
- Internal Auditors
- CFO/Director/Head of Accounting
- Business Analysts
- Data Analysts
- Banking and Accounting Analysts
- Certified Financial Analysts
- Credit Analysts
- Financial Advisors
- Math, Science and Commerce Graduates
- IT Security officials, IT Admin (Network, Firewall, System Admin), IT professionals
- Mid-level Executives
- Information Security
- Information Law
AI & Deep Learning Training Modules in Singapore
This module commences with an introduction to AI and Deep Learning. You will essentially learn the various concepts of artificial intelligence and neural networks and how Deep Learning solves problems that Machine Learning cannot. The modules take you through the fundamentals of Machine Learning, Artificial neural networks, and Multilayer Perceptron. You will also be introduced to Python libraries like TensorFlow, OpenCV, and Keras. The modules also explain how deep networks are capable of discovering patterns in data and by using TensorFlow learn how to build a Multi-layer perceptron and convolutional neural networks in Python. Students will enjoy trying to solve real-time problems by applying deep learning to different data types and through deep architectures, such as convolutional networks, recurrent networks, and autoencoders.
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 Singapore
Artificial Intelligence has been a sizzling subject for all industries in recent times and it is predicted that 85% of all emerging technologies will have some AI foundations by 2022. 75% of people in the world already use AI in some form and this incorporation of Artificial Intelligence with all existing and emerging technologies is only increasing year by year. Some of the trends that will dominate the 2020s will include AI-enabled chips which will generate a revenue of $95,105 Million by 2025. These AI-enabled chips will boost the performance of tasks requiring AI applications such as facial recognition, natural language processing, object detection, computer vision, etc. The other trend buzzing around is the coming together of Artificial Intelligence and the Internet of Things, a match made in digital heaven. With IoT devices and collecting data and Artificial Intelligence algorithms using that data to create useful results and Smart Home Devices are the best example of the use of this technology that is producing smart products like thermostats, alarm systems, doorbells, etc.
The trend that will completely revolutionize the current market and create new methods of improvement will be the integration of Artificial Intelligence and Cloud Computing that will help companies avail the benefits of Artificial Intelligence through the cloud despite not having massive computing power and access to large data sets. The popular cloud leaders in the market that have incorporated AI into their cloud services are Amazon Web Service (AWS), Google, IBM, etc. With the rise in complexity and magnitude of cyberattacks, the strength of artificial intelligence when combined with cybersecurity is adding more resources to combat with vulnerable networks and cyber attackers. A survey on AI adoption had Singapore in third place in the Asia Pacific region for organizational AI adoption (10.1%). Portcast is a startup in Singapore that uses predictive analytics with real-time signals so that maritime companies can better forecast cargo flows. Singapore is steadily marching towards AI adoption, where machines are ready to do our work. Join the course on AI & Deep Learning in Singapore and be ready to work on machines to get it right.
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