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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-for-marketing/
课程评论：没有评论
课程名称：无代码人工智能营销 课程概述： 本课程旨在帮助您了解如何利用人工智能为您的营销策略增添竞争优势，课程不需要任何编程知识。您将学习如何创建复杂的机器学习模型，掌握数据的收集和清洗、算法选择、模型训练、评估和部署等技能，所有这些都不需要代码。 主要学习内容包括： 1. **预测分析**：学习如何预测客户流失、销售额、广告活动表现、媒体购买组合、市场篮子分析和潜在客户评分。 2. **聚类/细分**：了解如何创建用户聚类，以最大化投资回报率，在合适的时机向合适的客户传达正确的信息。 3. **自然语言处理**：掌握使用NLP进行情感分析、竞争研究、趋势分析及客户反馈分析的技能。 4. **心理画像个性化**：学习如何揭示用户的心理特征，以预测用户行为和消费偏好，基于心理画像实时细分用户并个性化网站，以提供超个性化的体验。 5. **计算机视觉**：通过视觉社交聆听，掌握如何利用视觉数据进行个性化，实施电商店铺的视觉搜索，检测标志、情绪，给图像分配标签，理解图像中的文本。 6. **人工智能营销自动化聊天机器人**：学习如何创建一个基于AI的聊天机器人，它能够根据之前的客户查询自我学习，从而帮助您扩展业务、节省时间和成本，提高客户满意度，增加客户互动，并监测消费者数据以获得洞察。 通过本课程，您将掌握当前市场中最热门的技能，使您在营销领域中脱颖而出。
Learn how to embrace AI for MarketingGive your marketing strategy an unfair advantage by learning how to leverage artificial intelligence. No coding needed!Create sophisticated machine learning models understand how to gather and clean data, select an algorithm, train, evaluate and deploy amodel without code. Acquire the most in demand skillsPredictive AnalyticsLearn how to predict churn, sales, advertising campaign performance, media buying mix, market basket analysis, lead scoring…Clustering/SegmentationLearn how to create clusters to maximize your ROI. Show the right message to the right customer at the right moment.Natural Language ProcessingLearn how to use NLP for sentiment analysis, competition research, trend analysis, customer feedback analysisPsychographic PersonalizationLearn how to reveal user psychographics to predict user behavior and consumption preferences, segment users and personalize your website in real time based on psychographics to deliver hyper-personalized experiences.Computer VisionDrive visual social listening, learn how to use visual data for personalization, implement visual search for an ecommerce store. Detect logos, emotions, assign labels, understand text from images using computer vision.AI Marketing Automation ChatbotLearn how to create an AI-powered chatbots that learns by itself based on previous customer queries. It can help you scale, save time, save cost, provide greater customer satisfaction, increase customer engagement, monitor consumer data to gain insights.
