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Where can I learn Robotics and Artificial Intelligence in Nigeria?. A vast area of computer science called artificial intelligence focuses on designing and creating intelligent machines that are capable of carrying out tasks that typically require human intelligence. Artificial intelligence refers to the capacity of a computer or a robot controlled by a computer to carry out tasks that are typically done by humans because they call for human intelligence and judgment. Robotics, on the other hand, is the area of technology that deals with the creation, use, and application of robots as well as the computer systems used to control, sense, and process information about them. Designing intelligent machines that can aid humans in their daily lives and ensure everyone’s safety is the aim of robotics. You absolutely must enroll in the artificial intelligence program. The goal of robotics is to create intelligent machines that can aid and assist humans in their daily lives while also keeping everyone safe. It is critical that you enroll in the artificial intelligence and robotics training at Deejoft Technology Coding School in Ibadan, Nigeria because Deejoft Technology Coding School will immerse you completely in the world of artificial intelligence and robotics.

You will also learn about artificial intelligence and robotics use cases and applications, as well as concepts and terms such as machine learning, deep learning, and neural networks during this training at Deejoft Technology Coding School. You will be exposed to a variety of issues and concerns surrounding artificial intelligence and robotics, as well as receive advice from experts on how to learn and begin a career in AI. Deejoft Technology will be teaching you how to use the necessary tools pertaining to this field of technology, and also inform you of the various career opportunities available to you. Of course, technology is now a major stronghold in today’s world; most businesses and companies must now install computers and robots to alleviate work-related stress. Certainly, there is a compelling need for you to pursue artificial intelligence and robotics training in Deejoft Technology Coding School Nigeria.

Where can I learn Robotics and Artificial Intelligence in Nigeria?. Are robotics and artificial intelligence the same thing?

Though the terms are sometimes (incorrectly) used interchangeably, robotics and artificial intelligence are not the same thing. Artificial intelligence is the process by which systems mimic the human mind in order to learn, solve problems, and make decisions on the fly without the need for pre-programmed instructions. Robotics is the study of the construction and programming of robots to perform specific tasks. In most cases, this simply doesn’t require artificial intelligence, as the tasks performed are predictable, repetitive and don’t need additional ‘thought’.

Where can I learn Robotics and Artificial Intelligence in Nigeria?. Artificial intelligence and robotics strongholds

They are significant branches that guide the field of artificial intelligence and robotics.

Machine Learning

Through the use of machine learning, which is a form of artificial intelligence, software programs can predict outcomes more accurately without being explicitly instructed to do so. In order to forecast new output values, machine learning algorithms use historical data as input. Fraud detection, spam filtering, malware threat detection, business process automation, and predictive maintenance are all areas where machine learning is used. Machine learning is significant because it aids in the development of new products and provides businesses and organizations with a view of trends in consumer behavior and business operational patterns. Machine learning is a key component of operations for many of today’s top businesses. For many businesses, machine learning has emerged as a key competitive differentiator.

Advanced Learning

Advanced Learning is a type of artificial intelligence and machine learning that mimics how people learn specific types of information. Data science, which also includes statistics and predictive modeling, includes deep learning as a key component. Deep learning is very helpful for data scientists because it speeds up and simplifies the process of gathering, analyzing, and interpreting large amounts of data.

Synthetic neural network

Synthetic neural network is a hardware and/or software system designed to mimic the operation of neurons in the human brain. They are computing systems inspired by the biological neural networks that comprise brains and are commonly referred to as neural networks. The foundation of an artificial neural network is a collection of connected units or nodes known as artificial neurons, which loosely model the neurons in a biological brain. These technologies are typically used to solve complex signal processing or pattern recognition problems. Handwriting recognition for check processing, speech-to-text transcription, oil-exploration data analysis, weather prediction, and facial recognition are examples of significant commercial applications.

Artificial intelligence and robotics tools

Tensor flow

TensorFlow is one of the most popular and well-known machine learning and deep learning tools available among the various open-source platforms. With all of its features, it still has the adaptability to work in a variety of use case scenarios. Tensorflow is an open-source library for large-scale machine learning and numerical computation that makes it easier for Google Brain TensorFlow to gather data, train models, deliver predictions, and improve future outcomes. Machine learning and deep learning models and algorithms are combined in Tensorflow. Additionally, tensor flow is used in the fields of sentiment analysis, self-driving cars, text summarization, image/video recognition, and speech recognition systems.

MxNet

MxNet permits the use of a forgetful back prop to exchange computation time for memory. When dealing with a recurrent net that is in a lengthy sequence, this is especially helpful. The tool has been designed for scalability and supports multi-machine and multi-GPU training with ease. It has features like the ability to write custom layers in a high-level language.

PyTorch

PyTorch is a tensor library optimized for Deep Learning applications that use GPUs and CPUs. It is an open-source Python machine learning library created primarily by the Facebook AI Research team.

Scikit-learn

The most effective and reliable Python machine learning library is scikit learn. Through a consistent Python interface, it offers a variety of effective tools for statistical modeling and machine learning, including dimensionality reduction, clustering, and classification. Scikit-learn machine learning applications are used for product development, neuroimaging, barcode scanner development, medical modeling, financial cybersecurity analytics, and assistance with Shopify inventory problems.

Theano

The Keras is wrapped in the Theano. Keras is a Python library that allows for deep learning and runs on Tensorflow or Theano. Theano was created to create models of profound learning that are simple and quick to implement in some innovative work.

Keras

Keras is ideal if you enjoy using Python and the way it operates. Theano and Tensorflow, which are used in the backend, are used by this high-end library to handle neural networks. It selects the architecture that is appropriate for specific problems. By using images with weights, it helps identify issues. It sets up a network to optimize results. For performance or compatibility, Keras offers a very abstract structure that can be translated to any other framework.

Where can I learn Robotics and Artificial Intelligence in Nigeria?. Opportunities in artificial intelligence and robotics

Deejoft Technology Coding School will also walk you through the career opportunities available to you after completing the artificial intelligence and robotics training. The following are some examples of common jobs for skilled individuals with knowledge of artificial intelligence and robotics, along with a brief job description for each role.

Program Developer

A program developer’s primary responsibilities are as follows: Examining current systems. Providing suggestions for system improvements, including cost estimates. Collaboration with analysts, designers, and staff. Creating detailed specifications and writing program code. Before going live, the product should be tested in controlled, real-world scenarios. User training manuals are being prepared. After the systems are up and running, they must be maintained.

Data Engineer

A data engineer’s primary duties include the following: deciding on and incorporating any Big Data frameworks and tools necessary to deliver requested capabilities. putting ETL into practice. Keeping an eye on performance and suggesting any infrastructure changes that may be required. establishing data retention guidelines.

Robotics programmer

Lines of code are written by the robotics programmer in order to communicate with the robot and instruct it to perform specific tasks.

Machine Learning Engineer

A machine learning engineer’s primary duties include the following: using a programming language with machine learning libraries to conduct machine learning experiments. implementing production-ready machine learning solutions. improving the scalability and performance of solutions.

Studying scientist

The studying scientist is responsible for finding solutions to research issues for which we currently do not have answers. taking part in cutting-edge research on applications of machine learning and intelligence. implementation, measurement, iteration, and prototyping.

Business Intelligence Developer

The following are the primary duties of a business intelligence developer: creating, building, and maintaining data models for sophisticated, scalable, and extensible cloud-based data platforms. creating and upkeep of the conceptual, logical, and physical levels of the enterprise data model. establishing models for data security, quality, load, transport, and performance while defining common metrics and measurements.