This course is the perfect introduction to Data Analysis for those looking to start a career in the field. It covers the role of a Data Analyst, the tools used, and the skills and responsibilities required. You will learn about the data ecosystem, Big Data platforms, and the fundamentals of the data analysis process. With the help of data experts, you will gain tips and advice to start your career. The final project will test your knowledge and provide a real-world scenario of data analysis tasks. No prior experience is necessary. Start your journey into Data Analysis today!
Google Data Analytics Capstone: Complete a Case Study
4.8
Coursera304,770 learners
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This Google Data Analytics Capstone course is the eighth course in the Google Data Analytics Certificate. It provides learners with the opportunity to complete an optional case study, which will help prepare them for the data analytics job hunt. Learners will be guided by current Google data analysts to learn how to ask questions, prepare, process, analyze, visualize and act on data from a chosen analytics-based scenario. They will also gain valuable job hunt skills such as common interview questions and responses, materials to build a portfolio online, and more. By the end of this course, learners will be equipped to apply for introductory-level jobs as data analysts with no previous experience necessary. Sign up now to learn the benefits and uses of case studies and portfolios in the job search, explore real world job interview scenarios, and complete your own case study for your portfolio.
Python Project for Data Science
4.5
Coursera146,951 learners
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This mini-course is the perfect opportunity to demonstrate your foundational Python skills for working with data. You will assume the role of a Data Scientist or Data Analyst and be provided with a real-world data set and scenario to identify patterns and trends. You will use libraries such as Pandas and Beautiful Soup within a Jupyter Notebook to extract data, web scrape, visualize data and create a dashboard. Upon completion, you will have an impressive project to add to your job portfolio. Pre-requisite: Python for Data Science AI and Development course from IBM is a must for this project course. Don't miss out on this chance to showcase your Python proficiency and take your data science skills to the next level!
Tools for Data Science
4.5
Coursera391,145 learners
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This course provides an introduction to the popular tools used by Data Science professionals. It covers the Data Scientist's tool kit, including libraries and packages, data sets, machine learning models, kernels, and open source, commercial, big data, and cloud-based tools. Through hands-on experience, learners will develop skills for working with these tools, including Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. At the end of the course, learners will create a final project with a Jupyter Notebook, demonstrating their proficiency in preparing a notebook, writing Markdown, and sharing their work with peers. With the tools hosted in the cloud on Skills Network Labs, learners will be able to test each tool and follow instructions to run simple code in Python, R, or Scala.
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