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所在平台: Udemy |
课程主页: https://www.udemy.com/course/21-data-science-portfolio-projects-in-21-days/
课程评论：没有评论
课程名称：21天内完成21个数据科学项目 概述：此综合数据科学课程设计为一次为期21天的强化学习旅程，涵盖机器学习和人工智能领域中最相关和最需求的主题。每天集中实施一个完整的项目，旨在提升您的技术技能和专业作品集。课程内容从基础概念到高级应用合乎逻辑地逐步推进。 **第一周（第1-7天）：** - 开始进行时间序列预测，使用ARIMA模型 - 掌握客户分析和细分 - 开发信用风险模型 - 构建社交媒体情感分析器 - 创建电子商务推荐系统 - 设计员工流失预测模型 - 实施房地产定价模型 **第二周（第8-14天）：** - 开发网络安全威胁检测系统 - 创建欺诈检测算法 - 建立能源消费预测模型 - 设计交通流量预测系统 - 计算客户终身价值 - 分析股票市场模式 - 实施自然语言处理文本分类 **第三周（第15-21天）：** - 进行市场篮分析 - 创建健康风险预测模型 - 构建音乐流派分类器 - 预测房地产市场趋势 - 开发自动交易系统 - 掌握使用Prophet进行需求预测 - 利用强化学习构建AI代理 每个项目均采用行业标准的工具和框架，包括： - Python编程语言 - 常用库如Scikit-learn、TensorFlow和PyTorch - 数据处理工具如Pandas和NumPy - 可视化库包括Matplotlib和Seaborn - 高级机器学习框架，如Prophet和NLTK 课程包括： - 随时可观看的视频内容 - 所有项目的可下载源代码 - 实际数据集以进行实践体验 - 互动编码练习 - 基于项目的评估 - 结业证书 所有材料反映了最新的行业实践和技术进步，适用于数据科学和机器学习领域。
This comprehensive data science course is structured as an intensive 21-day journey through the most relevant and in-demand areas of machine learning and artificial intelligence. Each day focuses on a complete project implementation, carefully designed to build both your technical skills and your professional portfolio.The curriculum progresses logically from foundational concepts to advanced applications:**Week 1 (Days 1-7):**- Begin with time series forecasting using ARIMA- Master customer analytics and segmentation- Develop credit risk models- Build social media sentiment analyzers- Create e-commerce recommendation systems- Design employee attrition predictors- Implement real estate pricing models**Week 2 (Days 8-14):**- Develop cybersecurity threat detection systems- Create fraud detection algorithms- Build energy consumption forecasting models- Design traffic flow prediction systems- Calculate customer lifetime value- Analyze stock market patterns- Implement NLP text classification**Week 3 (Days 15-21):**- Conduct market basket analysis- Create health risk prediction models- Build music genre classifiers- Forecast housing market trends- Develop automated trading systems- Master demand forecasting with Prophet- Build AI agents using reinforcement learningEach project utilizes industry-standard tools and frameworks including:- Python programming language- Popular libraries like Scikit-learn, TensorFlow, and PyTorch- Data manipulation tools like Pandas and NumPy- Visualization libraries including Matplotlib and Seaborn- Advanced ML frameworks such as Prophet and NLTKThe course includes:- On-demand video content- Downloadable source code for all projects- Real-world datasets for practical experience- Interactive coding exercises- Project-based assessments- Certificate of completionAll materials reflect the latest industry practices and technological advances in the field of data science and machine learning.
