|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/time-series-analysis-real-world-projects-in-python/
课程评论：没有评论
课程名称：Python中的时间序列分析与实际项目 课程概述：你是否希望获得一份高薪的工作，专注于数据科学、人工智能及时间序列分析与预测？或者你是一名经验丰富的AI从业者，想提升自己的职业生涯？又或是你是一名热切的数据科学家，渴望获得实际的数据科学和时间序列分析技能？如果以上问题的答案是“是”，那么本课程正是为你而设！本课程将教授你必要的实践技能，使你能够胜任定量金融分析师、数据分析师或数据科学家的职位。在商业中，数据科学和人工智能被应用于优化业务流程、最大化收入和降低成本。本课程旨在以实用、轻松和有趣的方式，让你掌握数据科学与时间序列分析在商业中的关键应用知识。课程提供实际的动手经验，使用真实世界的数据集。 欢迎来到学习如何使用Python编程语言进行时间序列分析的最佳在线资源！课程将教会你使用Python进行时间序列数据预测的所有知识，帮助你预测未来的数据点。 任务包括： 1. 任务#1：预测温度：开发一个时间序列模型来预测温度。 2. 任务#2：预测Covid-19病例：使用Prophet开发时间序列模型，预测Covid-19病例。 3. 任务#3：预测股票价格：使用时间序列算法预测股票价格。 通过这个课程，你将获得在数据科学领域成功所需的实际技能和信心！
Are you looking to land a top-paying job in Data Science , AI & Time Series Analysis & Forecasting?Or are you a seasoned AI practitioner who want to take your career to the next level?Or are you an aspiring data scientist who wants to get Hands-on Data Science and Time Series Analysis?If the answer is yes to any of these questions, then this course is for you!This course will teach you the practical skills that would allow you to land a job as a quantitative financial analyst, a data analyst or a data scientist.In business, Data Science , AI is applied to optimize business processes, maximize revenue and reduce cost. The purpose of this course is to provide you with knowledge of key aspects of data science & Time Series applications in business in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets.Welcome to the best online resource for learning how to use the Python programming Language for Time Series Analysis!This course will teach you everything you need to know to use Python for forecasting time series data to predict new future data points.1.Task #1 @Predicting the Temperature : Develop an Time Series model to predict Temperature..3.Task #2 @Predict Covid-19 Cases: Develop Time Series Model using Prophet that can predict Covid-19 cases2.Task #3 @Predict the Stock Prices: Predict the prices of stock using Time Series Algorithms.
