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所在平台: Udemy |
课程主页: https://www.udemy.com/course/become-a-data-analyst-job-training-beginner-to-advanced-gate-moyyn/
课程评论：没有评论
课程名称：成为数据分析师 - 职业培训（初级到高级） 概述： 欢迎参加《数据分析师职业培训》课程，这是一个首创的短期项目，专为求职者和转行者设计。该课程专注于工作导向的培训，教授与实际工作环境相关的概念，旨在帮助希望进入数据分析领域或希望获得该领域首个实践经验的学生。该项目将教你如何满足数据分析师职位的要求，培养与实际工作相关的技能。 课程要点： 1. 数据采集：从多种来源获取和收集数据，并确保数据的准确性和完整性。 2. 数据清洗：清理和预处理数据，为分析做好准备。 3. 报告和可视化：创建报告和仪表板以呈现关键绩效指标（KPI）和数据驱动的见解。 4. 统计分析：运用统计方法进行数据分析，得出可执行的见解。 5. 假设检验和回归分析：根据需要进行深入分析，实施和维护数据质量标准。 课程内容： - 如何在Python中导入数据，使用Kaggle。 - 数据处理：处理分布、异常值、空值和缺失值。 - 深入理解描述性统计。 - 掌握数据可视化：图表用法及适用场景。 - 了解推论统计：假设检验、正态分布、中心极限定理、样本与总体、抽样、检验统计量、I型和II型错误。 - 学习和应用预测分析。 学习工具： - Pandas、Numpy、Matplotlib、Seaborn、PythonPlotlyDash等。 额外模块与福利： 1. 人工智能基础与应用：获得与AI模块的专属访问权限，学习如何利用AI提升工作效率，并了解AI在各行业的应用。 2. 职业指导：了解如何有效求职、寻找初创企业、撰写精彩的简历和求职信，以及各类求职平台。 讲师介绍： 1. Dr. Chetana Didugu - 数据科学家、产品专家，来自德国，拥有超过10年的行业经验，曾在亚马逊等顶尖企业工作。 2. Aravinth Palaniswamy - 德国和印度两国的初创企业创始人，技术顾问，拥有10年以上风险投资、产品及增长营销经验。 此课程为希望进入数据分析及相关领域的学习者提供了一条明确且实践性强的学习路径。
Welcome to 'Data Analyst - Job training', a first-of-its kind short program designed for jobseekers and career change aspirants. This course is specifically created as a JOB-BASED TRAINING program thereby teaching concepts hands-on and relevant to real-work environment. If you are looking for a job in Data Analysis or if you are a student who would like to get first experience in this domain, this course is exactly for you. How is this program a JOB-BASED TRAINING and how will it equip you with skills relevant for your role:What companies ask for a Data Analyst role? Gather and collect data from various sources, ensuring data accuracy and completeness.Clean and preprocess data to prepare it for analysis.Clean and preprocess data to prepare it for analysis.Create reports and dashboards to present key performance indicators (KPIs) and data-driven insights.Apply statistical methods to analyze data and derive actionable insights.Conduct hypothesis testing and regression analysis as needed.Implement and maintain data quality standards.How this course meets the requirements?Learn how to import data in Python, usiung kaggleLearn how to treat input data: distribution, outliers, null and missing valuesGain a deeper understanding in Descriptive StatisticsMaster Data visualisation: Graphing etiquettes - which graphs are applicable for what type of data analysisGain knowledge on Descriptive Statistics, Inferential Statistics and Predictive StatisticsUnderstand Inferential statistics: Hypothesis testing, Normal distribution, Central LImit Theorem, Sample vs Population, Sampling, test statistics, Type I and II errorLearn and work with predictive analysisTools you will learn: PandasNumpy functionsStatistics MatplotlibSeabornPythonplotlydashMatplotlibData VisualisationExtra Module and Benefits:1. AI Fundamentals and Applications: Unlock exclusive access to one of our AI modules Learn from our experts leveraging AI to enhance your productivity and understand the wide variety of applications of AI across industries2. Career GuidanceUnderstand how to effectively search for a job, find startups, craft a compelling CV and Cover Letter, types of job platforms and many more!Trainers:Dr. Chetana Didugu - GermanyDr. Chetana Didugu is an Experienced Data Scientist, Product Expert, and PhD graduate from IIM Ahmedabad. She has worked 10+ years in various top companies in the world like Amazon, FLIX, Zalando, HCL, etc in topics like Data Analysis and Visualisation, Business Analysis, Product Management, Product Analytics & Data Science. She has trained more than 100 students in this domain till date.Aravinth Palaniswamy - GermanyFounder of 2 startups in Germany and India, Technology Consultant, and Chief Product Officer of Moyyn, and has 10+ years of experience in Venture Building, Product and Growth Marketing.
