|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-python-and-sql-boot-camp-with-projects-hindi/
课程评论：没有评论
课程名称：数据科学：Python 和 SQL 实战训练营（附项目） 课程概述：该训练营旨在帮助学生全面掌握数据科学的基础知识，特别适合在印度以外的学生。由于应用程序和网站受限于 OTP 的原因，无法访问课程。此训练营提供一个可及的、结构化的学习体验。课程内容涵盖数据分析、可视化及机器学习的核心概念，学习者将从基础开始，获得实际操作经验，使用 Pandas、NumPy、Matplotlib、Seaborn 和 Scikit-learn 等工具进行真实世界项目的实践。 课程适合初学者及有志于成为数据科学家的学生，通过生动的实例和印地语讲解，简化复杂主题。学员将通过以下行业导向的项目培养必要的问题解决技能： 1. **Zomato 案例研究**：进行深入的探索性数据分析（EDA），创建基于真实 Zomato 数据集的可视化，分析餐饮业务趋势、客户偏好及不同城市的外卖模式。 2. **Uber 案例研究**：项目从数据清洗步骤开始，包括处理缺失值、格式不一致（如时间戳）及去重。接着应用数据处理技术，如特征提取（日期、时间、位置）和分类，培养学员在整理混乱数据、提取商业洞察和创建数据故事方面的基础技能，这些对数据分析师及未来数据科学家至关重要。 3. **Airbnb 案例研究**：通过处理真实的 Airbnb 数据集，模拟典型的数据科学工作流。项目聚焦于严格的数据清洗（处理缺失值、修复不一致性、格式化数据类型）和数据处理（特征工程、数据过滤和分组），帮助学生在数据准备方面打下坚实基础，为提取可操作的商业洞察提供训练，从而帮助平台优化房源、定价和用户体验。 无论您是希望从事数据科学的工作，还是希望增强分析技能，此训练营都将为您提供必需的工具和技术。立即加入，借助专家指导、实用项目和结构化学习路径来转变您的职业生涯！
Master Data Science with Python and SQL in this comprehensive Hindi boot camp! Designed especially for students outside India who are unable to access courses through our application and website due to OTP restrictions, this boot camp provides an accessible and structured learning experience.Learn key concepts from scratch, including data analysis, visualization, and machine learning. Gain hands-on experience with real-world projects using Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn. Explore SQL for data manipulation, querying, and database management.This course simplifies complex topics with practical examples and Hindi explanations, making it ideal for beginners and aspiring data scientists. Develop essential problem-solving skills by working on industry-oriented projects:Zomato Case Study - In this project, we perform an in-depth exploratory data analysis (EDA) and create insightful visualizations based on a real-world Zomato dataset. The aim is to understand restaurant business trends, customer preferences, and food delivery patterns across different cities.Uber Case Study - The project starts with data cleaning steps such as handling missing values, correcting inconsistent formats (like timestamps), and removing duplicates. Then, data processing techniques like feature extraction (day, time, location from timestamps) and categorization are applied. This project builds strong foundational skills in preparing messy real-world data, deriving meaningful business insights, and creating impactful data stories - skills essential for both data analysts and aspiring data scientists.Air BNB Case Study - In this project, we work with a real-world Airbnb dataset to simulate a typical data science workflow. Starting with raw, messy data, we focus on rigorous data cleaning (handling missing values, fixing inconsistencies, formatting data types) and data processing (feature engineering, filtering, and grouping data). This project helps students strengthen their foundation in data preparation - the most critical step in data science - and trains them to extract actionable business insights to help platforms like Airbnb optimize listings, pricing, and user experience.Whether you aim for a job in data science or want to strengthen your analytical skills, this boot camp equips you with the essential tools and techniques. Join now and transform your career with expert guidance, practical projects, and a structured learning path!"
