Artificial Intelligence CourseHow to apply AI to Programmatic Buying
What is an Artificial Intelligence course? If you are interested in topics such as Machine Learning and Deep Learning, and if you wish to begin your journey into AI education, whether through a free training course or a master’s degree, it’s crucial to find a course that provides a comprehensive understanding of this intricate subject.
Our Artificial Intelligence course includes a thorough explanation of what an AI is and how it can be trained using various Learning Models.
The fundamentals of an Artificial Intelligence Course
An artificial intelligence course content must immediately and easily explain what is meant by AI and what is the foundation of its Learning.
Artificial Intelligence (AI) refers to the simulation of Human Intelligence in Machines (e.g. Computers or Robots) programmed to think like humans and mimic their actions.
It is based on the principle that human intelligence can be defined in such a way that a machine can easily imitate it and perform tasks, from the simplest to the most complex.
The fundamental question from which Artificial Intelligence starts is therefore: can machines think? To ensure that an AI can autonomously solve problems of various kinds through reasoning, it will have to be trained through Learning Models.
Learning Models for human-like machine intelligence
The main objective of Artificial Intelligence is to train machines using specific Learning Models, typically exclusive algorithms, to simulate human reasoning. These models enable the creation of intelligent machines, our AIs, which can effectively respond to diverse scenarios beyond the algorithms used to construct them, ensuring the best possible reactions to external stimuli.
A comprehensive Artificial Intelligence course should elucidate how to train machines based on specific learning model, ensuring that an effective AI becomes proficient in executing tasks and functions similar to those performed by humans, such as:
- Acting humanly (i.e. indiscriminately with respect to a human being);
- Thinking humanly (solving a problem with cognitive functions);
- Thinking rationally (i.e. using logic similar to that of a human being);
- Acting rationally (performing a process to obtain the best expected result based on the information available).
There are two types of learning applicable to an Artificial Intelligence:
- Machine Learning;
- Deep Learning
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Machine Learning and real-world implementation in artificial intelligence
Machine Learning is a foundational aspect of our Artificial Intelligence course: it enables AI systems to learn, develop, and make decisions autonomously through data analysis. It empowers computers and robots to perform tasks in a manner resembling human learning from experience.
An in-depth AI course should explore how Machine Learning trains AI to respond to stimuli through three types of learning: supervised, unsupervised, and reinforcement.
Machine Learning examples
Examples of Machine Learning applications include voice recognition technology in smartphones, smart home automation, and autonomous car driving. The former uses supervised machine learning with pre-packaged models, while the latter exemplifies reinforcement learning, requiring advanced systems like sensors and cameras for environment understanding.
Machine Learning also finds application in marketing and communication, including personalized advertising and real-time bidding. The future of marketing will cater to individual users with the help of bots, enhancing user interactions with online services.
Our course will also delve into Weak AI, simulating human cognitive functions without achieving true human intellect. Unlike Strong AI, Weak AI requires human intervention and lacks autonomous thinking.
Deep Learning in AI: what it is it and how it relates to Strong Artificial Intelligence
Deep Learning, a subcategory of Machine Learning, is closely related to the field of Artificial Intelligence. Its main purpose is to create Learning Models on multiple levels, which involve learning from data using statistical calculation algorithms rather than relying on data explicitly provided by humans, as in traditional Machine Learning.
Artificial Intelligence trained with Deep Learning Models possesses the ability to classify incoming and outgoing data, highlighting relevant information for problem-solving and disregarding irrelevant data. This capability grants the AI a human-like capacity to learn concepts from pre-established schemes to complex forms of reasoning, allowing it to independently detach and improve increasingly complex functions.
Deep Learning Examples
Deep Learning is already applied in various fields, going beyond science fiction. For instance, E-Commerce systems utilize it to personalize the customer purchase based on individual preferences. Online Machine Translation Services, like Google Translate, benefit from Deep Learning, continuously learning from user feedback to enhance translation accuracy over time.
Facebook‘s success in showing products and services aligned with users’ interests and instantly identifying and removing inappropriate content is attributed to Artificial Intelligence trained through Deep Learning Models.
If you’re looking for an Artificial Intelligence Course, make sure it contains insights and substantial examples regarding this fascinating branch of AI.
Deep Learning and Strong AI
Deep Learning leads to the creation of Strong Artificial Intelligence (or Strong AI), often referred to as Wise Systems. Strong AI can develop its intelligence autonomously without emulating human thought processes or cognitive abilities.
A Machine trained with Deep Learning becomes a cognitive entity with capacities indistinguishable from humans.
A high-quality artificial intelligence course should elucidate the concept of Strong AI and draw comparisons with Weak AI, as discussed previously.
Machine Learning Models: the importance of data scientist
Our Artificial Intelligence course will cover the development of Learning Models, specifically those related to Machine Learning, which is the domain of a Data Scientist.
The Data Scientist identifies the necessary data for training Machine Learning Models, defines their attributes, and selects the appropriate models to utilize.
Our Course on Artificial Intelligence aims to equip participants with the expertise in Machine Learning, enabling them to analyze and handle vast Data Sets using technologies like Azure Machine Learning (AML) Service, AutoML, HyperDrive, and more
Simplify Machine Learning with Python and ready-made templates
Python is a versatile and dynamic object-oriented programming language suitable for various software development tasks. It serves as an excellent choice for programming beginners who wish to explore Machine Learning and Data Science.
Being minimalist and intuitive, Python offers ready-made Libraries and Modules that facilitate the creation of Machine Learning Templates covering the entire cycle of a Machine Learning Project. This process generally includes five steps:
- Define the problem;
- Prepare data;
- Evaluate algorithms;
- Improve results;
- Present results.
Our Artificial Intelligence course includes a dedicated section on developing Machine Learning Models with Python, accompanied by explanatory tutorials.
Don’t miss this opportunity to delve into the world of AI and enhance your expertise!
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The artificial neural networks
Deep Learning connects our AI with the human mind, enabling brain-like reasoning.
At the core of Deep Learning AI are Artificial Neural Networks – advanced computing models emulating human brain neurons during learning and recognition. These networks allow programmers to train the machine with different types of experience, enabling correct responses to new data.
AI learns through experience via the Neural Network, not just programmed as in Machine Learning.
Matlab: creating Surface Neural Networks
Our comprehensive AI Course includes Deep Learning examples and tutorials for creating Surface Neural Networks using Matlab. Surface Neural Networks are easy to create, with two or three levels of data connections.
Matlab, an environment for numerical calculations and statistical analysis, offers Toolboxes for Machine Learning, Deep Learning, and Artificial Neural Networks of various complexities.
Creating a neural network with Matlab is straightforward, even for less experienced individuals.
Artificial Neural Networks empower AI to learn from data, recognize patterns, classify data, and predict future events. Deep Learning Models, unlike simpler ones in Machine Learning, can have many layers, necessitating in-depth AI training to understand their structure and creation through Matlab tutorials.
Objectives of our artificial intelligence course and its structure
Our journey to understand how to start an Artificial Intelligence Course concludes with a program that covers all essential points. This ensures extensive training on Artificial Intelligence, Machine Learning, and Deep Learning, accessible even for beginners in the field.
Digital Coach’s AI course details
- Module 1: What is Programmatic Buying and what is it based on;
- Module 2: Automating the Buying and Selling of Advertisements in the Digital Age;
- Module 3: Programmatic Buying strategies and when to use them;
- Module 4: What is Real Time Bidding (RTB) and how it works;
- Module 5: Platforms: What They Are and What Features They Have;
- Module 6: How to optimize advertising campaigns;
- Module 7: Setting up a real advertising campaign.
Whether you opt for a Degree Course in Artificial Intelligence, a Digital Marketing Course, or a Free Course focused on RTB, including any of these points will provide an excellent starting point to explore the diverse nuances and applications of the intriguing yet complex subject of Artificial Intelligence.
Who is our Artificial Intelligence course designed for?
- Employees of marketing offices specialized in online advertising;
- Freelancers who want to expand their skills;
- Entrepreneurs who want to manage their online advertising;
- Young individuals entering the professional world with new digital professions.
Artificial Intelligence course fees and modes
The course of Programmatic Buying and RTB 1st part will last 3.5 hours. You may attend the lecture ON DEMAND from the comfort of your home at a cost of € 95.00 + VAT. You can choose the day and time, and you will also have the opportunity to review the lesson whenever and wherever you want.
You can pay by credit card or PayPal. If you would like to participate in the course, simply fill in the contact form below and specify in the message”Registration for REAL TIME BIDDING & PROGRAMMATIC BUYING“.
Some of the most important question about Artificial Intelligence
Are there any prerequisites for enrolling in the Artificial Intelligence course?
Completing an Artificial Intelligence course can open up a wide range of career opportunities. Some common career paths include AI engineer, machine learning engineer, data scientist, research scientist, AI consultant, and AI project manager. The demand for AI professionals is rapidly growing across industries.
Can the Artificial Intelligence course help in starting a career transition into AI?
Yes, an Artificial Intelligence course can be beneficial for individuals looking to transition into a career in AI. It provides the necessary knowledge and skills to enter the field and demonstrates a commitment to learning and professional development in AI.
How can the knowledge gained from the Artificial Intelligence course be applied in real-world scenarios?
The knowledge gained from an Artificial Intelligence course can be applied in various real-world scenarios. It can be used to develop AI-powered applications, implement machine learning algorithms for data analysis, enhance automation processes, create intelligent chatbots, optimize business operations, and more.
Can Artificial Intelligence replace human jobs?
Artificial Intelligence has the potential to automate certain tasks and job functions, leading to changes in the job market. While AI may eliminate some repetitive or manual tasks, it can also create new job roles and opportunities.