Artificial Intelligence (AI) Training Courses

Artificial Intelligence (AI) Training Courses

Local instructor-led live Artificial Intelligence (AI) training courses in Қазақстан.

Artificial Intelligence (AI) Course Outlines

Course Name
Duration
Overview
Course Name
Duration
Overview
7 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at software engineers or anyone who wish to learn how to use Vertex AI to perform and complete machine learning activities. By the end of this training, participants will be able to:
  • Understand how Vertex AI works and use it as a machine learning platform.
  • Learn about machine learning and NLP concepts.
  • Know how to train and deploy machine learning models using Vertex AI.
7 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at biologists who wish to understand how AlphaFold works and use AlphaFold models as guides in their experimental studies. By the end of this training, participants will be able to:
  • Understand the basic principles of AlphaFold.
  • Learn how AlphaFold works.
  • Learn how to interpret AlphaFold predictions and results.
14 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at data analysts and data scientists who wish to use Weka to perform data mining tasks. By the end of this training, participants will be able to:
  • Install and configure Weka.
  • Understand the Weka environment and workbench.
  • Perform data mining tasks using Weka.
14 hours
The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
21 hours
In this instructor-led, live training in Қазақстан, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data. By the end of this training, participants will be able to:
  • Implement machine learning algorithms and techniques for solving complex problems.
  • Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
  • Push Python algorithms to their maximum potential.
  • Use libraries and packages such as NumPy and Theano.
21 hours
It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data. This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements. By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.
Format of the Course
  • Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
28 hours
The aim of this course is to provide general proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
28 hours
This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.
35 hours
This is a 5 day introduction to Data Science and Artificial Intelligence (AI). The course is delivered with examples and exercises using Python 
28 hours
This is a 4 day course introducing AI and it's application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course. 
21 hours
Deep Reinforcement Learning refers to the ability of an "artificial agent" to learn by trial-and-error and rewards-and-punishments. An artificial agent aims to emulate a human's ability to obtain and construct knowledge on its own, directly from raw inputs such as vision. To realize reinforcement learning, deep learning and neural networks are used. Reinforcement learning is different from machine learning and does not rely on supervised and unsupervised learning approaches. In this instructor-led, live training, participants will learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent. By the end of this training, participants will be able to:
  • Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning
  • Apply advanced Reinforcement Learning algorithms to solve real-world problems
  • Build a Deep Learning Agent
Audience
  • Developers
  • Data Scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
14 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at data scientists who wish to use IBM Cloud Pak to prepare data for use in AI solutions. By the end of this training, participants will be able to:
  • Install and configure Cloud Pak for Data.
  • Unify the collection, organization and analysis of data.
  • Integrate Cloud Pak for Data with a variety of services to solve common business problems.
  • Implement workflows for collaborating with team members on the development of an AI solution.
28 hours
In this instructor-led, live training in Қазақстан, participants will learn how to implement deep learning models for telecom using Python as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of deep learning.
  • Learn the applications and uses of deep learning in telecom.
  • Use Python, Keras, and TensorFlow to create deep learning models for telecom.
  • Build their own deep learning customer churn prediction model using Python.
14 hours
Embedding Projector is an open-source web application for visualizing the data used to train machine learning systems. Created by Google, it is part of TensorFlow. This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project. By the end of this training, participants will be able to:
  • Explore how data is being interpreted by machine learning models
  • Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it
  • Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals.
  • Explore the properties of a specific embedding to understand the behavior of a model
  • Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
7 hours
This course has been created for managers, solutions architects, innovation officers, CTOs, software architects and anyone who is interested in an overview of applied artificial intelligence and the nearest forecast for its development.
21 hours
This course uses a practical approach to teaching OptaPlanner. It provides participants with the tools needed to perform the basic functions of this tool.
28 hours
This four day course is aimed at teaching how genetic algorithms work; it also covers how to select model parameters of a genetic algorithm; there are many applications for genetic algorithms in this course and optimization problems are tackled with the genetic algorithms.
7 hours
This is a classroom based training session in a presentation and Q&A format
14 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at technical persons who wish to set up or extend an RPA system with more intelligent capabilities. By the end of this training, participants will be able to:
  • Install and configure UiPath IPA.
  • Enable robots to manage other robots.
  • Apply computer vision to locate screen objects with accuracy.
  • Enable robots that can detect language patterns and carry out sentiment analysis on unstructured content.
14 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at software testers who wish to have an AI driven software testing environment. By the end of this training, participants will be able to:
  • Automate unit test generation and parameterization with AI.
  • Apply machine learning learning in a real world use-case.
  • Automate the generation and maintenance of API tests with AI.
  • Use machine learning methods to self-heal the execution of Selenium tests.
7 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at marketers who wish to use AI to improve improve digital marketing strategies through valuable customer insights. By the end of this training, participants will be able to:
  • Leverage AI software to improve the way brands connect to users.
  • Use chatbots to optimize the user-experience.
  • Increase productivity and revenue through the automation of tasks.
28 hours
Microsoft Azure Cloud offerings are the most comprehensive set of services w.r.t. AI, ML, DL From Vision, Speech to Language to Conversational bots, Azure is empowering organizations to process their data to derive insights This instructor-led, live training (online or onsite) is aimed at AI enthusiasts who wish to use Azure to build AI scenarios in the cloud By the end of this training, participants will be able to:
  • Build Azure based AI scenarios.
  • Understand the end to end functioning of API based infering
  • Build conversational bots for business needs
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request more details or customized training for this course, please contact us to arrange.
21 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at engineers who wish to program and create robots through basic AI methods. By the end of this training, participants will be able to:
  • Implement filters (Kalman and particle) to enable the robot to locate moving objects in its environment.
  • Implement search algorithms and motion planning.
  • Implement PID controls to regulate a robot's movement within an environment.
  • Implement SLAM algorithms to enable a robot to map out an unknown environment.
7 hours
This instructor-led, live training in Қазақстан (online or onsite) is aimed at managers and business leaders who wish to learn about the fundamentals of artificial intelligence and manage AI projects for their organization. By the end of this training, participants will be able to understand AI at a technical level and strategize using their organization’s data and resources to successfully manage AI projects.
80 hours
In this instructor-led, live training in Қазақстан (online or onsite), participants will learn the different technologies, frameworks and techniques for programming different types of robots to be used in the field of nuclear technology and environmental systems. The 4-week course is held 5 days a week. Each day is 4-hours long and consists of lectures, discussions, and hands-on robot development in a live lab environment. Participants will complete various real-world projects applicable to their work in order to practice their acquired knowledge. The target hardware for this course will be simulated in 3D through simulation software. The code will then be loaded onto physical hardware (Arduino or other) for final deployment testing. The ROS (Robot Operating System) open-source framework, C++ and Python will be used for programming the robots. By the end of this training, participants will be able to:
  • Understand the key concepts used in robotic technologies.
  • Understand and manage the interaction between software and hardware in a robotic system.
  • Understand and implement the software components that underpin robotics.
  • Build and operate a simulated mechanical robot that can see, sense, process, navigate, and interact with humans through voice.
  • Understand the necessary elements of artificial intelligence (machine learning, deep learning, etc.) applicable to building a smart robot.
  • Implement filters (Kalman and Particle) to enable the robot to locate moving objects in its environment.
  • Implement search algorithms and motion planning.
  • Implement PID controls to regulate a robot's movement within an environment.
  • Implement SLAM algorithms to enable a robot to map out an unknown environment.
  • Test and troubleshoot a robot in realistic scenarios.
120 hours
In this instructor-led, live training in Қазақстан (online or onsite), participants will learn the different technologies, frameworks and techniques for programming different types of robots to be used in the field of nuclear technology and environmental systems. The 6-week course is held 5 days a week. Each day is 4-hours long and consists of lectures, discussions, and hands-on robot development in a live lab environment. Participants will complete various real-world projects applicable to their work in order to practice their acquired knowledge. The target hardware for this course will be simulated in 3D through simulation software. The ROS (Robot Operating System) open-source framework, C++ and Python will be used for programming the robots. By the end of this training, participants will be able to:
  • Understand the key concepts used in robotic technologies.
  • Understand and manage the interaction between software and hardware in a robotic system.
  • Understand and implement the software components that underpin robotics.
  • Build and operate a simulated mechanical robot that can see, sense, process, navigate, and interact with humans through voice.
  • Understand the necessary elements of artificial intelligence (machine learning, deep learning, etc.) applicable to building a smart robot.
  • Implement filters (Kalman and Particle) to enable the robot to locate moving objects in its environment.
  • Implement search algorithms and motion planning.
  • Implement PID controls to regulate a robot's movement within an environment.
  • Implement SLAM algorithms to enable a robot to map out an unknown environment.
  • Extend a robot's ability to perform complex tasks through Deep Learning.
  • Test and troubleshoot a robot in realistic scenarios.
7 hours
The training is aimed at people who want to learn the basics of neural networks and their applications.
14 hours
This course is an introduction to applying neural networks in real world problems using R-project software.
14 hours
This training course is for people that would like to apply Machine Learning in practical applications. Audience This course is for data scientists and statisticians that have some familiarity with statistics and know how to program R (or Python or other chosen language). The emphasis of this course is on the practical aspects of data/model preparation, execution, post hoc analysis and visualization. The purpose is to give practical applications to Machine Learning to participants interested in applying the methods at work. Sector specific examples are used to make the training relevant to the audience.
21 hours
Artificial Neural Network is a computational data model used in the development of Artificial Intelligence (AI) systems capable of performing "intelligent" tasks. Neural Networks are commonly used in Machine Learning (ML) applications, which are themselves one implementation of AI. Deep Learning is a subset of ML.

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