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所在平台: Udemy |
课程主页: https://www.udemy.com/course/become-a-data-scientist/
课程评论：没有评论
课程名称：成为数据科学家：SQL、Tableau、机器学习与深度学习 [4合1] 课程概述： 如果你是一个渴望学习者，想要深入探索数据科学的奇妙世界，那么这门课程就是为你量身定制的！这门课程将帮助你掌握数据科学职业所需的基本技能，特别是SQL、Tableau、使用Python的机器学习和深度学习。如果你的答案是“是的”，那么请加入我们，开始成为数据科学家的旅程！ 在这门课程中，你将全面了解使用Python进行SQL、Tableau、机器学习和深度学习。你将培养分析数据、可视化洞察、构建预测模型和得出可操作商业解决方案的必要技能。以下是课程的一些关键收益： - 精通SQL、Tableau、机器学习和深度学习 - 建立数据分析、数据可视化和数据建模的坚实基础 - 获得处理现实世界数据集的实践经验 - 深入理解机器学习和深度学习的基本概念 - 学习使用Python构建和训练自己的预测模型 课程内容： 1. **SQL for Data Science**：学习数据分析所需的SQL技能，包括基本的数据操作和高级主题如子查询、连接、数据聚合等。 2. **Data Visualization Using Tableau**：掌握如何开发引人注目的仪表板和可视化，能够有效地探索、分析和沟通数据。 3. **Machine Learning Using Python**：提供Python快速入门课程，学习如何预处理数据并构建不同的回归和分类模型。 4. **Deep Learning Using Python**：学习创建神经网络以发现数据中的复杂模式，构建卷积神经网络进行图像识别。 课程特色： 通过实际活动，你将在课程中建立SQL数据库、创建交互式仪表板、实施各种机器学习算法和构建深度学习模型。课程由具备丰富数据科学经验的行业专家教授，并结合了实用的商业分析内容，确保你获得全面的学习体验。 我们承诺： 如有任何课程内容或相关问题，请随时在课程中提问或直接发送消息给我们。不要错过成为数据科学家的机会，现在就注册并开始你充实的职业旅程！
If you are a curious learner looking to dive into the exciting world of data science, then this course is tailor-made for you! Do you want to master the essential skills required for a successful career in data science? Are you eager to develop expertise in SQL, Tableau, Machine and Deep Learning using Python? If your answer is a resounding "yes," then join us and embark on a journey towards becoming a data scientist!In this course, you will gain a comprehensive understanding of SQL, Tableau, Machine Learning, and Deep Learning using Python. You will develop the necessary skills to analyze data, visualize insights, build predictive models, and derive actionable business solutions. Here are some key benefits of this course:Develop mastery in SQL, Tableau, Machine & Deep Learning using PythonBuild strong foundations in data analysis, data visualization, and data modelingAcquire hands-on experience in working with real-world datasetsGain a deep understanding of the underlying concepts of Machine and Deep LearningLearn to build and train your own predictive models using PythonData science is a rapidly growing field, and there is a high demand for skilled professionals who can analyze data and provide valuable insights. By learning SQL, Tableau, Machine & Deep Learning using Python, you can unlock a world of career opportunities in data science, AI, and analytics.What's covered in this course?The analysis of data is not the main crux of analytics. It is the interpretation that helps provide insights after the application of analytical techniques that makes analytics such an important discipline. We have used the most popular analytics software tools which are SQL, Tableau and Python. This will aid the students who have no prior coding background to learn and implement Analytics and Machine Learning concepts to actually solve real-world problems of Data Science.Let me give you a brief overview of the coursePart 1 - SQL for data scienceIn the first section, i.e. SQL for data analytics, we will be teaching you everything in SQL that you will need for Data analysis in businesses. We will start with basic data operations like creating a table, retrieving data from a table etc. Later on, we will learn advanced topics like subqueries, Joins, data aggregation, and pattern matching.Part 2 - Data visualization using TableauIn this section, you will learn how to develop stunning dashboards, visualizations and insights that will allow you to explore, analyze and communicate your data effectively. You will master key Tableau concepts such as data blending, calculations, and mapping. By the end of this part, you will be able to create engaging visualizations that will enable you to make data-driven decisions confidently.Part 3 - Machine Learning using PythonIn this part, we will first give a crash course in python to get you started with this programming language. Then we will learn how to preprocess and prepare data before building a machine learning model. Once the data is ready, we will start building different regression and classification models such as Linear and logistic regression, decision trees, KNN, random forests etc.Part 4 - Deep Learning using PythonIn the last part, you will learn how to make neural networks to find complex patterns in data and make predictive models. We will also learn the concepts behind image recognition models and build a convolutional neural network for this purpose. Throughout the course, you will work on several activities such as:Building an SQL database and retrieving relevant data from itCreating interactive dashboards using TableauImplementing various Machine Learning algorithmsBuilding a Deep Learning model using Keras and TensorFlowThis course is unique because it covers the four essential topics for a data scientist, providing a comprehensive learning experience. You will learn from industry experts who have hands-on experience in data science and have worked with real-world datasets.What makes us qualified to teach you?The course is taught by Abhishek (MBA - FMS Delhi, B. Tech - IIT Roorkee) and Pukhraj (MBA - IIM Ahmedabad, B. Tech - IIT Roorkee). As managers in the Global Analytics Consulting firm, we have helped businesses solve their business problems using Analytics and we have used our experience to include the practical aspects of business analytics in this course. We have in-hand experience in Business Analysis.We are also the creators of some of the most popular online courses - with over 1,200,000 enrollments and thousands of 5-star reviews like these ones:This is very good, i love the fact the all explanation given can be understood by a layman - JoshuaThank you Author for this wonderful course. You are the best and this course is worth any price. - DaisyOur PromiseTeaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet, or anything related to any topic, you can always post a question in the course or send us a direct message.Don't miss out on this opportunity to become a data scientist and unlock your full potential! Enroll now and start your journey towards a fulfilling career in data science.
