The global market for Artificial Intelligence technologies is expected to grow by more than 40% by 2026 - This is one of the fastest-growing sectors in the tech world, creating a surge in demand for skilled AI professionals across all industries, as this cutting-edge field is at the forefront of technological innovation, driving unprecedented advancements across diverse sectors.
Throughout the course program, you will acquire in-depth knowledge in topics such as machine learning, natural language processing, deep learning, and advanced data analysis. You will engage in hands-on projects, operate leading industry tools, gain an understanding of how to effectively implement these technologies across a variety of industries, and upon graduation, will become a highly sought-after professional, equipped with the skills to drive change through advanced AI applications.
The global AI market size is projected to grow from $387.45 billion in 2022 to $1,394.30 billion by 2029, at a CAGR of 20.1% in the forecast period (source: Fortune Business Insights). This explosive growth is creating a surge in demand for skilled AI professionals across all industries.
As AI becomes more pervasive, there's an increasing focus on responsible AI development, addressing issues such as bias mitigation, privacy protection, and the societal impact of AI technologies.
Our comprehensive course is designed to equip you with the knowledge, skills, and practical experience needed to thrive in this rapidly evolving field. As the demand for AI and machine learning experts is becoming increasingly high, now is your chance to enhance your existing technical skillset, obtain a solid foundation and cutting-edge expertise in ML and AI, and power your value and contribution across industries.
Programming Tools and Languages
Skills & Techniques
Develop and deploy scalable ML models to solve complex business problems, optimizing performance and ensuring seamless integration with existing systems.
Push the boundaries of AI technology by designing novel algorithms, conducting experiments, and publishing cutting-edge research in areas like deep learning and natural language processing.
Create innovative visual recognition systems for applications ranging from autonomous vehicles to medical imaging, leveraging state-of-the-art deep learning techniques.
AI & Machine Learning Track: From Novice to Expert
Launch your career in AI & Machine Learning with our most comprehensive educational track. This program is meticulously designed to provide you with an all-encompassing understanding of the field, ensuring you achieve the highest level of expertise.
Key Features:
This track is your gateway to becoming a proficient AI & Machine Learning expert, equipping you with the knowledge, skills, and hands-on experience needed to excel in this rapidly evolving and in-demand area of technology.
| Machine Learning & Data Science | Course duration | |
|---|---|---|
| Machine Learning Fundamentals Course | 25 academic hours | |
This course presents the theory and fundamentals of Machine Learning, as well as recommended working methods for ML. | ||
| Scientific Python Course | 30 academic hours | |
The "Scientific Python" course at RTG College is part of an advanced learning program that equips students with the necessary skills for advanced analysis of scientific data. Throughout the course, students develop proficiency in the Python programming language and practice using libraries like NumPy, Pandas, and Matplotlib for data processing and analysis. The knowledge is conveyed through hands-on projects, allowing students to apply the knowledge and develop solution-focused abilities in a practical environment. At the end of the course, students conduct in-depth analysis and present their findings in a final project. The course provides you with the tools for breakthroughs in the complex world of data analysis. | ||
| Machine Learning With Python Course | 50 academic hours | |
Python offers a wide range of libraries that can be used for Machine Learning (such as NumPy, SciPy, Matplotlib). In this course, you will learn how to implement the tools from these libraries. Using these tools, we will also implement models that were taught in previous courses. | ||
| Deep Learning with TensorFlow Course | 50 academic hours | |
Deep Neural Networks draw inspiration from the way the human brain functions and represent the most advanced subset of Artificial Intelligence. In this course, you will learn how to develop and test Deep Learning models using the TensorFlow / Keras platforms for Machine Learning and Neural Networks projects. | ||
| Software Programming Courses | Course duration | |
| Python Course | 90 academic hours | |
The focus is on Python 3, aiming to provide the knowledge and experience required for programming real-world applications in an object-oriented industry. You will learn how to develop software using Python. You will be taught techniques and appropriate tools to professionally develop high-level Python programs suitable for high-tech companies. This is a very practical course in which we will also be using circuit boards. Python is currently considered one of the most popular and sought-after programming languages in the IT industry. Its popularity and widespread use in various industry projects make Python one of the most demanded programming courses. The high demand and diverse employment opportunities make Python highly beneficial to specialize in for a rewarding professional career with multiple growth opportunities. | ||
| SQL Course | 30 academic hours | |
In this course, you will learn and practice SQL (Structured Query Language) and gain thorough familiarity with MySQL. The goal of the course is to learn how to communicate and perform various operations with the database. Most software operates with large amounts of data in the background. Nowadays, this data can be stored in different types of databases, like MySQL or Oracle in the backend. During software testing, some of this data needs to be verified, for example, to check if the relevant data is stored correctly in the databases. Therefore, knowledge of database basics and SQL queries is essential. In the course, we will cover topics such as SQL Formal Definitions, The Relational Model, SQL Key Notes, SQL Properties, SQL User Objective, Data Definition Language, and more. | ||
| AWS Course | 35 academic hours | |
The course is designed to help you gain a deep understanding of the architectural principles and services of Amazon Web Services (AWS). You will learn how to design and deploy AWS cloud applications using recommended best practices endorsed by Amazon. | ||
| GIT (Version Control) Course | 25 academic hours | |
Git is an open-source version control system that serves as a tool for managing code versions and the software development process. Its primary purpose is to help developers efficiently manage code and track changes in software files. In this course, you will learn the core features of Git, workflow techniques, and methods to undo changes or maintain multiple project versions. Additionally, you'll discover how to collaborate effectively with other teams and developers. Designed for programmers seeking the best and most suitable way to manage code development versions, the course covers essential workflow principles, core features, version control, collaboration, and more. | ||
Tuition: $14800.00 $10800.00
AI & Machine Learning Specialist Track
Elevate your software development expertise with our focused AI & Machine Learning program. This track is carefully crafted for professionals with prior experience in software and application development, aiming to sharpen your skills in this specialized domain.
Key Features:
This track offers a streamlined path to mastering AI & Machine Learning , ideal for seasoned developers looking to expand their expertise or pivot into this high-demand field. Gain the specific knowledge and skills needed to excel in AI & Machine Learning development and stand out in the competitive tech industry.
| Machine Learning & Data Science | Course duration | |
|---|---|---|
| Machine Learning Fundamentals Course | 25 academic hours | |
This course presents the theory and fundamentals of Machine Learning, as well as recommended working methods for ML. | ||
| Scientific Python Course | 30 academic hours | |
The "Scientific Python" course at RTG College is part of an advanced learning program that equips students with the necessary skills for advanced analysis of scientific data. Throughout the course, students develop proficiency in the Python programming language and practice using libraries like NumPy, Pandas, and Matplotlib for data processing and analysis. The knowledge is conveyed through hands-on projects, allowing students to apply the knowledge and develop solution-focused abilities in a practical environment. At the end of the course, students conduct in-depth analysis and present their findings in a final project. The course provides you with the tools for breakthroughs in the complex world of data analysis. | ||
| Machine Learning With Python Course | 50 academic hours | |
Python offers a wide range of libraries that can be used for Machine Learning (such as NumPy, SciPy, Matplotlib). In this course, you will learn how to implement the tools from these libraries. Using these tools, we will also implement models that were taught in previous courses. | ||
| Deep Learning with TensorFlow Course | 50 academic hours | |
Deep Neural Networks draw inspiration from the way the human brain functions and represent the most advanced subset of Artificial Intelligence. In this course, you will learn how to develop and test Deep Learning models using the TensorFlow / Keras platforms for Machine Learning and Neural Networks projects. | ||
Tuition: $6800.00
Customizable AI & Machine Learning Expertise Track
Tailor your tech education with our flexible, modular program. This track allows you to focus on specific areas of interest, creating a personalized learning journey.
Key Features:
| Machine Learning & Data Science | Course duration | |
|---|---|---|
| Machine Learning Fundamentals Course | 25 academic hours | |
This course presents the theory and fundamentals of Machine Learning, as well as recommended working methods for ML. | ||
| Scientific Python Course | 30 academic hours | |
The "Scientific Python" course at RTG College is part of an advanced learning program that equips students with the necessary skills for advanced analysis of scientific data. Throughout the course, students develop proficiency in the Python programming language and practice using libraries like NumPy, Pandas, and Matplotlib for data processing and analysis. The knowledge is conveyed through hands-on projects, allowing students to apply the knowledge and develop solution-focused abilities in a practical environment. At the end of the course, students conduct in-depth analysis and present their findings in a final project. The course provides you with the tools for breakthroughs in the complex world of data analysis. | ||
| Machine Learning With Python Course | 50 academic hours | |
Python offers a wide range of libraries that can be used for Machine Learning (such as NumPy, SciPy, Matplotlib). In this course, you will learn how to implement the tools from these libraries. Using these tools, we will also implement models that were taught in previous courses. | ||
| Deep Learning with TensorFlow Course | 50 academic hours | |
Deep Neural Networks draw inspiration from the way the human brain functions and represent the most advanced subset of Artificial Intelligence. In this course, you will learn how to develop and test Deep Learning models using the TensorFlow / Keras platforms for Machine Learning and Neural Networks projects. | ||
| Software Programming Courses | Course duration | |
| Python Course | 90 academic hours | |
The focus is on Python 3, aiming to provide the knowledge and experience required for programming real-world applications in an object-oriented industry. You will learn how to develop software using Python. You will be taught techniques and appropriate tools to professionally develop high-level Python programs suitable for high-tech companies. This is a very practical course in which we will also be using circuit boards. Python is currently considered one of the most popular and sought-after programming languages in the IT industry. Its popularity and widespread use in various industry projects make Python one of the most demanded programming courses. The high demand and diverse employment opportunities make Python highly beneficial to specialize in for a rewarding professional career with multiple growth opportunities. | ||
| SQL Course | 30 academic hours | |
In this course, you will learn and practice SQL (Structured Query Language) and gain thorough familiarity with MySQL. The goal of the course is to learn how to communicate and perform various operations with the database. Most software operates with large amounts of data in the background. Nowadays, this data can be stored in different types of databases, like MySQL or Oracle in the backend. During software testing, some of this data needs to be verified, for example, to check if the relevant data is stored correctly in the databases. Therefore, knowledge of database basics and SQL queries is essential. In the course, we will cover topics such as SQL Formal Definitions, The Relational Model, SQL Key Notes, SQL Properties, SQL User Objective, Data Definition Language, and more. | ||
| AWS Course | 35 academic hours | |
The course is designed to help you gain a deep understanding of the architectural principles and services of Amazon Web Services (AWS). You will learn how to design and deploy AWS cloud applications using recommended best practices endorsed by Amazon. | ||
| GIT (Version Control) Course | 25 academic hours | |
Git is an open-source version control system that serves as a tool for managing code versions and the software development process. Its primary purpose is to help developers efficiently manage code and track changes in software files. In this course, you will learn the core features of Git, workflow techniques, and methods to undo changes or maintain multiple project versions. Additionally, you'll discover how to collaborate effectively with other teams and developers. Designed for programmers seeking the best and most suitable way to manage code development versions, the course covers essential workflow principles, core features, version control, collaboration, and more. | ||
Course cost: $10,800
Alex Shoihat
Head of Machine Learning
Alex holds a B.Sc. in Information Systems and an M.A. in Electrical and Electronic Engineering.
As a Machine Learning Engineer at Embedded Academy, Alex specializes in the field of artificial intelligence, applying over 13 years of experience in project development, management, and transitioning from development to production in various domains such as Linux Embedded.
Throughout his career, Alex developed his expertise working with the integration of Machine Learning and Deep Learning in the Computer Vision and Data Analysis field.
Students must complete the following to be eligible for AI & ML certification:
As part of the professional experience each graduate undergoes we help in integrating them into the high-tech world through our job search assistance, personalized resume building, and placement in a technology company.
1
Curriculum customization
We'll help you choose and structure the right program most suitable for your needs and career aspirations.
2
Tech Training
Students who start with no prior knowledge of the field will receive the fundamentals required to complete the course.
3
Final Project
Working on your course project and internship with experienced developers.
4
Internship
Get real-world experience adapted to industry standards and requirements with our team of industry-leading engineers.
5
Job Interview
Graduates get resume-building assistance, interview simulations and career guidance.
Shaked Laivo
Full Stack course graduate
Lina Tomkov
Automation course graduate
Automation Engineer, Mohican Lab
Dima Solomianik
Real Time Embedded course graduate
RT Embedded Engineer, HP
Alex K.
Real Time Embedded course graduate
Linux Kernel Developer
Mia S.
Cybersecurity course graduate
Incident Response Specialist
Sarah L.
Machine Learning course graduate
AI/ML developer
Tom R.
Full Stack course graduate
Full Stack developer
James H.
DevOps course graduate
DevOps developer, Quali
David M.
Embedded System course graduate
Embedded System engineer
Emma W.
IT course graduate
Linux Administrator, HP
The admission requirements for the Artificial Intelligence Development program are as follows:
The field of artificial intelligence is gaining increasing significance across a wide range of life domains. As a result, there is a growing demand from tech companies for skilled professionals in this field. Leading companies in finance, healthcare, cybersecurity, autonomous vehicle development, and more are constantly seeking skilled artificial intelligence (AI) engineers.
The training program includes hands-on practical work in order to gain experience in development, not just theoretical knowledge. This is to acquire relevant experience in the field for immediate employment and career start upon completion of studies.
Homework assignments, portfolio development, and knowledge assessments are integral parts of the program structure. They are designed to align with industry requirements and professionally provide the learned material and relevant knowledge for the demands of the high-tech industry.
Currently, classes in the Artificial Intelligence program take place online.
