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In these comprehensive video courses, created by Santiago Basulto, you will learn the whole process of data analysis. You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn, Additionally, we've included a thorough Jupyter Notebook course, and a quick Python reference to refresh your programming skills.
- Course related:
- AMA1600 Fundamentals of AI and Data Analytics and AMA1751 Linear Algebra
- Subjects:
- Computing, Data Science and Artificial Intelligence and Mathematics and Statistics
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Others
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Video
Gradient Descent is the workhorse behind most of Machine Learning. When you fit a machine learning method to a training dataset, you're probably using Gradient Descent. It can optimize parameters in a wide variety of settings. Since it's so fundamental to Machine Learning, I decided to make a "step-by-step" video that shows you exactly how it works.
- Course related:
- COMP4434 Big Data Analytics
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Machine learning Computer algorithms
- Resource Type:
- Video
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Video
Statistics, Machine Learning and Data Science can sometimes seem like very scary topics, but since each technique is really just a combination of small and simple steps, they are actually quite simple. My goal with StatQuest is to break down the major methodologies into easy to understand pieces. That said, I don't dumb down the material. Instead, I build up your understanding so that you are smarter.
- Course related:
- HTI34016 Introduction to Clinical Research
- Subjects:
- Computing, Data Science and Artificial Intelligence and Mathematics and Statistics
- Keywords:
- Machine learning Mathematical analysis Statistics Data mining
- Resource Type:
- Video
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Courseware
This course is for all of those struggling with data analysis. You will learn: - Overcome data analysis challenges in your work and research - Increase your productivity and make better business decisions - Enhance your data analysis skills using spreadsheets - Learn about advanced spreadsheet possibilities like array formulas and pivottables - Learn about Excel 2013 features like PowerPivot & PowerMap - Learn to organize and test your spreadsheets
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Courseware
This course covers the main tasks required from data analysts today, including importing, summarizing, interpreting, analyzing and visualizing data. It aims to equip you with the tools that will enable you to be an independent data analyst. Most techniques will be taught in Excel with add-ons and free tools available online. You will learn: - How to make data come to life with well-known types of visualizations such as line and bar graphs and new types of visualizations such as spark lines, contour plots and population pyramids. - How to create dashboards in Excel based on live data that can meet managerial and business needs. - How to connect data from different sources, such as the web and exports from your CRM, ERP, SAP or data warehouse. - Some hands-on data science and how to use actionable analysis tools. - Deep dive into known tools like PivotTables and introduce new ones like the analysis toolpak
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Courseware
Are you ready to leave the sandbox and go for the real deal? Have you followed Data Analysis: Take It to the MAX() and Data Analysis: Visualization and Dashboard Design and are ready to carry out more robust data analysis? In this project-based course you will engage in a real data analysis project that simulates the complexity and challenges of data analysts at work. Testing, data wrangling, Pivot Tables, sparklines? Now that you have mastered them you are ready to apply them all and carry out an independent data analysis. For your project, you will pick one raw dataset out of several options, which you will turn into a dashboard. You will begin with a business question that is related to the dataset that you choose. The datasets will touch upon different business domains, such as revenue management, call-center management, investment, etc.
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Courseware
While big data infiltrates all walks of life, most firms have not changed sufficiently to meet the challenges that come with it. In this course, you will learn how to develop a big data strategy, transform your business model and your organization. This course will enable professionals to take their organization and their own career to the next level, regardless of their background and position. Professionals will learn how to be in charge of big data instead of being subject to it. In particular, they will become familiar with tools to: - assess their current situation regarding potential big data-induced changes of a disruptive nature, - identify their options for successfully integrating big data in their strategy, business model and organization, or if not possible, how to exit quickly with as little loss as possible, and - strengthen their own position and that of their organization in our digitalized knowledge economy The course will build on the concepts of product life cycles, the business model canvas, organizational theory and digitalized management jobs (such as Chief Digital Officer or Chief Informatics Officer) to help you find the best way to deal with and benefit from big data induced changes. During the course, your most pressing questions will be answered in our feedback videos with the lecturer. In the assignments of the course, you will choose a sector and a stakeholder. For this, you will develop your own strategy and business model. This will help you identify the appropriate organizational structure and potential contributions and positions for yourself.
- Subjects:
- Computing, Data Science and Artificial Intelligence and Management
- Keywords:
- Business -- Data processing Big data
- Resource Type:
- Courseware