人工智能辅导课程 | Artificial Intelligence (AI)辅导课程

由讲师进行实时指导的人工智能 培训课程导通过动手实践演示如何实施人工智能解决方案以解决实际问题。

人工智能培训形式包括“现场实时培训”和“远程实时培训”。现场实时培训可在客户位于中国的所在场所或考而思教育位于中国的企业培训中心进行，远程实时培训可通过交互式远程桌面进行。

AI(ArtificialIntelligence)课程大纲

Artificial Intelligence Overview

7小时 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.

Machine Learning Fundamentals with Python

14小时 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.

Python用于高级机器学习

21小时 在这一由讲师引导的现场培训中，参与者将学习Python中最相关及最尖端的机器学习技术，因为它们构建了一系列涉及图像、音乐、文本和财务数据的演示应用程序。在本次培训结束后，参与者将能够：- 运用用于解决复杂问题的机器学习算法和技术- 将深度学习和半监督学习应用于涉及图像、音乐、文本和财务数据的应用程序- 推动Python算法达到其最大潜力- 使用例如NumPy和Theano的库和包受众- 开发人员- 分析师- 数据科学家课程形式- 部分讲座、部分讨论、练习和大量实操

Machine Learning with Python

28小时 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.

Natural Language Processing with Python

28小时 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.

Introduction to Data Science and AI (using Python)

35小时 This is a 5 day introduction to Data Science and Artificial Intelligence (AI).The course is delivered with examples and exercises using Python

Applied AI from Scratch in Python

28小时 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.

用Python进行深度强化学习

21小时 深度强化学习是指“人工智能体”通过反复试验和奖惩来学习的能力。人工智能体旨在模仿人类直接从原始输入（如视觉）获取和构建知识的能力。为了实现强化学习，深度学习和神经网络会被用到。强化学习与机器学习不同，不依赖于有监督和无监督的学习方法。在这一由讲师引导的现场培训中，学员将在逐步创建深度学习智能体的过程中学习深度强化学习的基础知识。在本次培训结束后，学员将能够：- 理解深度强化学习的基本概念，及其与机器学习的区别- 运用先进的强化学习算法来解决实际问题- 构建深度学习智能体受众- 开发人员- 数据科学家课程形式- 部分讲座、部分讨论、练习和大量实操

用于电信行业的深度学习（使用Python）

28小时 机器学习是人工智能的一个分支，指计算机可以在不被明确编程的情况下学习。深度学习是机器学习的一个子领域，它使用基于学习数据表示和结构（例如神经网络）的方法。Python是一种高级编程语言，以其清晰的语法和代码易读性而闻名。在这一由讲师引导的现场培训中，学员将逐步学习如何创建深度学习信用风险模型，从而学习如何使用Python实现用于电信行业的深度学习模型。在本次培训结束后，学员将能够：- 了解深度学习的基本概念。- 了解深度学习在电信行业中的应用和用途。- 使用Python、Keras、TensorFlow创建用于电信行业的深度学习模型。- 使用Python构建自己的深度学习客户流失预测模型。课程形式- 互动讲座和讨论。- 大量练习和实操。- 在现场实验室环境中动手实现。课程自定义选项- 如需本课程的定制培训，请联系我们以作安排。

Fundamentals of Artificial Intelligence and Machine Learning

28小时 Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed.Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks.Python is a high-level programming language famous for its clear syntax and code readability.In this instructor-led, live training, 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.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 a customized training for this course, please contact us to arrange.

OptaPlanner in Practice

21小时 This course uses a practical approach to teaching OptaPlanner. It provides participants with the tools needed to perform the basic functions of this tool.

Genetic Algorithms

28小时 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.

AI in business and Society & The future of AI - AI/Robotics

7小时 This is a classroom based training session in a presentation and Q&A format

UiPath for Intelligent Process Automation (IPA)

14小时 This instructor-led, live training in 中国 (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.

Intelligent Testing

14小时 This instructor-led, live training in 中国 (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.

AI in Digital Marketing

7小时 This instructor-led, live training in 中国 (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.

IBM Cloud Pak for Data

14小时 This instructor-led, live training in 中国 (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.

Artificial Intelligence (AI) for Robotics

21小时 This instructor-led, live training in 中国 (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.

Artificial Intelligence (AI) for Managers

7小时 This instructor-led, live training in 中国 (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.

AI and Robotics for Nuclear

80小时 In this instructor-led, live training in 中国 (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.

AI and Robotics for Nuclear - Extended

120小时 In this instructor-led, live training in 中国 (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.

Introduction to the use of neural networks

7小时 The training is aimed at people who want to learn the basics of neural networks and their applications.

Neural Network in R

14小时 This course is an introduction to applying neural networks in real world problems using R-project software.

Applied Machine Learning

14小时 This training course is for people that would like to apply Machine Learning in practical applications.AudienceThis 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.

Artificial Neural Networks, Machine Learning, Deep Thinking

21小时 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.

From Zero to AI

35小时 This course is created for people who have no previous experience in probability and statistics.

Artificial Intelligence in Automotive

14小时 This course covers AI (emphasizing Machine Learning and Deep Learning) in Automotive Industry. It helps to determine which technology can be (potentially) used in multiple situation in a car: from simple automation, image recognition to autonomous decision making.

Neural Networks Fundamentals using TensorFlow as Example

28小时 This course will give you knowledge in neural networks and generally in machine learning algorithm, deep learning (algorithms and applications).This training is more focus on fundamentals, but will help you to choose the right technology : TensorFlow, Caffe, Teano, DeepDrive, Keras, etc. The examples are made in TensorFlow.

深度学习基础与实战

14小时

Pattern Recognition

21小时 This instructor-led, live course provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.The course is interactive and includes plenty of hands-on exercises, instructor feedback, and testing of knowledge and skills acquired.