AI data analytics course program
The training is conducted by Sardor Abdulkhamidov who has 8 years of experience in Python programming language and 6 years of work in AI; he is also the head of the "Innovative Development, Transport Logistics, Startup Management, Cybersport and Information Technologies” department at the Belarus-Uzbekistan Joint Polytechnic Institute; the UMDSOFT Project Manager; and, the Head of Burchak IT Company.
Dilshod Ikramov is our mentor, who will help you with self-study. Dilshod Ikramov has 4 years of experience in python programming and 2 years in AI, and 2 years in DevOps.
By the end of the course, you will:
1. Have a complete understanding of the problems of AI and how to solve them;
2. Understand the ways of working with a team of programmers and increasing interaction;
3. Develop a new software or create a new type of service based on new software;
4. Be able to propose new projects and programs for the Information Technology Market of Uzbekistan;
5. Develop the ability to implement your own startup (innovation in the world of IT) based on your gained knowledge and skills;
6. Have the ability to work on a real project;
7. Strengthen your knowledge through direct exchange of views with foreign experts.
Methodology
- Training sessions are based on active team exercises, interactive lectures, questions and answers, discussions and real projects.
- At the end of each month, an examination and interview process is carried out, which determines the level of knowledge of the practitioner and the state of readiness for the job.
- By the end of the course, individual projects will be given to each practitioner, which will serve to determine their ability to approach the tasks in the future.
- Successful graduates will be awarded certificates and the best graduates will be assisted in finding employment.
Modules
1.Introduction to Artificial Intelligence and Data Analytics. What is artificial intelligence, what is data analytic, and why is mathematical knowledge important in this field?
2. History, present and future of artificial intelligence and data analytics.
3. Artificial thinking, the creation and building of artificial intelligence.
4. Writing hardware-level code and creating a small virtual self-driving machine. Part 1.
5. Writing hardware-level code and creating a small virtual self-driving machine. Part 2.
7. Writing hardware-level code and creating a small virtual self-driving machine. Part 3.
8. Writing hardware-level code and creating a small virtual self-driving machine. Part 4
9. Working with the server and its settings, rules and technologies for creating a data center in the cloud.
10. Machine Learning and Deep Learning.
11. Deep Q-Learning Intuition.
12. Deep Convolutional Q-Learning Intuition.
Thank you for your interest in our training!