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Develop work-ready skills for an in-demand career as a data analyst. No degree or previous experience is required.
Gain the skills to work for an entry-level data analyst role through this eight-course Professional Certificate from IBM and position yourself competitively in the thriving job market for data analysts, which will see 20% growth to 2028 (U.S. Bureau of Labor Statistics).
Jumpstart your career as a data analyst by learning the basics of data analysis and gaining practical skills. You'll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics, gaining hands-on experience with data manipulation and the application of analytical techniques.
This Professional Certificate does not require any prior skills in programming or statistics, and is suitable for students with or without university degrees. Basic computer skills, high school math, comfort working with numbers, a willingness to learn, and a desire to enrich your profile with valuable skills are all you need to get started.
Upon successful completion of this program, you will have analyzed real-world data sets, created interactive dashboards, and presented reports to share your findings, giving you the confidence and portfolio to begin a career as an Associate or Junior Data Analyst. It will also create the foundation for other data disciplines, such as data science or data engineering.
Throughout the program, you will complete hands-on projects and labs and gain a firm grasp of the technical skills needed to effectively collect, discuss, mine and visualize data, as well as the soft skills to work with stakeholders and tell stories with data to Engage your audience.
At the end of the program, you'll complete a real-world capstone project designed specifically to showcase your newly learned data analyst skills.
All of these projects can be combined into a portfolio on GitHub or another service to clearly convey your experience and skills to potential employers.
This course presents a gentle introduction to data analysis concepts, the role of a data analyst, and the tools used to perform daily functions. You will gain an understanding of the data ecosystem and the fundamentals of data analysissuch as data collection or data mining. Next, you'll learn the soft skills required to effectively communicate your data to stakeholders, and how mastering these skills can empower you to become a data-driven decision maker.
This course will help you differentiate between the roles of data analyst, data scientist, and data engineer.. You will learn the responsibilities of a data analyst and exactly what data analysis entails. You will be able to summarize the data ecosystem, such as databases and data warehouses. You will then discover the top providers within the data ecosystem and explore the various on-premises and cloud tools. Continue this exciting journey and discover Big Data platforms like Hadoop, Hive, and Spark.
By the end of this course, you will be able to visualize the daily life of a data analyst, understand the different career paths that are available for data analysis, and identify the many resources available to master this profession. Throughout this course you will learn the key aspects of data analysis. You will begin to explore the basics of data collection and learn how to identify your data sources. Then you'll learn how to clean, analyze, and share your data using visualizations and dashboard tools.
All of this is combined into the final project, where you will test your knowledge of the course material, explore what it means to be a data analyst, and provide a real-world data analysis scenario. This course does not require prior experience in data analysis, spreadsheets, or computer science. All you need to get started is basic computer skills, high school math, and access to a modern web browser like Chrome or Firefox.
This course is designed to give you a basic working knowledge of using Excel spreadsheets for data analysis.. It covers some of the first steps in working with spreadsheets and their use in the data analysis process. It includes many videos, demos, and examples for you to learn, followed by step-by-step instructions for you to apply and practice in a live spreadsheet.
Excel is an essential tool for working with data, whether it's for business, marketing, data analysis, or research. This course is suitable for those who aspire to take up data analytics or data science as a profession., as well as for those who just want to use Excel for data analysis in their own domains. You'll gain valuable experience cleaning and managing data using functions, and then analyze your data using techniques like filtering, sorting, and creating pivot tables.
This course begins with an introduction to spreadsheets such as Microsoft Excel and Google Sheets and loading data from multiple formats. With this introduction, you'll learn how to perform some basic level data cleaning and sorting tasks and continue to expand your knowledge of data analysis through the use of filtering, sorting, and using pivot tables within the spreadsheet. By completing these tasks throughout the course, you will understand how spreadsheets can be used as a data analysis tool and understand their limitations. There is a strong focus on practice and applied learning in this course.
With each lab, you'll gain hands-on experience manipulating data and begin to understand the important role of spreadsheets. Clean and analyze your data faster by understanding the features in data formatting. Then, you'll turn your data into a pivot table and learn its features to keep your data organized and readable. The capstone project allows you to showcase your newly acquired data analysis skills.
By the end of this course, you will have worked with various data sets and spreadsheets and you'll have demonstrated the basics of data cleaning and analysis, all without having to learn any code. Getting started with Excel is easy in this course.
It does not require any prior experience with spreadsheets or coding. It also does not require downloads or installation of any software. All you need is a device with a modern web browser and the ability to create a Microsoft account to access Excel online at no cost. However, if you already have a desktop version of Excel, you can stick with it pretty easily as well.
This course covers some of the first steps in developing data visualization using spreadsheets. Start the process of turning your data into a story by learning about the different tools of a spreadsheet, like the important pivot function and the ability to create dashboards. Explore the many types of charts on offer and discover how each has its own unique property for transforming your data.. Take the course and gain valuable experience by becoming familiar with the popular analysis tool IBM Cognos Analytics. You'll end up with the knowledge of how to create a successful report, with the ability to communicate your findings.
Upon completion of this course, you will have a basic understanding of spreadsheets and how they can be used as a data visualization tool. You will gain the ability to effectively create data visualizations such as charts or graphs, and you will begin to see how they play a key role in communicating the findings of data analysis. All of this can be achieved by learning the basics of data analysis with Excel and IBM Cognos Analytics, without having to write any code.
By the end of this course, you will be able to describe common dashboard tools used by a data analyst, design and build a dashboard on a cloud platform, and begin to raise your level of confidence in creating intermediate-level data visualizations. Throughout this course, you will find 4 hands-on labs and a capstone project. With each lab, get hands-on experience creating basic and advanced charts, then continue with the course and start building dashboards with spreadsheets and IBM Cognos Analytics. Next, you will finish this course by creating a set of data visualizations with IBM Cognos Analytics and creating an interactive dashboard that can be shared with peers, professional communities, or potential employers.
This course does not require prior experience in data analysis, spreadsheets, or computer science. All you need to get started is basic computer skills, high school math, access to a modern web browser like Chrome or Firefox, and the ability to create a Microsoft account to access Excel for the web.
Start your learning Python for data science, as well as programming in general, with this introduction to Python for beginners. Python is one of the most popular programming languages in the world and there has never been a greater demand for professionals with the ability to apply the fundamentals of Python to drive business solutions across industries.
This course will take you from scratch to programming in Python in a matter of hours, no prior programming experience necessary! You'll learn the fundamentals of Python, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a capstone project to demonstrate your new skills.
By the end of this course, you will be comfortable creating basic programs, working with data, and solving real-world problems in Python. He will gain a solid foundation for further learning in the field and develop skills to help advance his career. This course can be applied to multiple specialization or professional certificate programs. Completion of this course will count toward your learning in any of the following programs: IBM Applied AI Professional Certificate Applied Data Science Specialization IBM Data Science Professional Certificate Upon completion of any of the above programs, in addition to earning a certificate of completion coursera specialization, you will also receive a digital badge from IBM that recognizes your expertise in the field.
Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language used to communicate with and extract data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist.
The purpose of this course is to introduce relational database concepts and help you learn and apply fundamental knowledge of the SQL language. It is also intended to help you get started with performing SQL access in a data science environment. The emphasis in this course is on hands-on learning.. As such, you'll work with real databases, real data science tools, and real-world data sets. You will create a database instance in the cloud. Through a series of labs, you will practice creating and executing SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python.
No prior knowledge of databases, SQL, Python, or programming is required. Anyone can audit this course free of charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is just $39 USD per month for access to qualifying materials and a certificate.
Learn to analyze data with Python. This course will take you from the basics of Python to exploring many different types of data. You'll learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
Topics covered: 1) Importing data sets 2) Cleaning the data 3) Manipulating the data frame 4) Summarizing the data 5) Building machine learning regression models 6) Building data pipelines Analyzing the data with Python will be delivered through lectures, labs, and assignments. It includes the following parts: Data Analysis Libraries - You will learn how to use the Pandas, Numpy, and Scipy libraries to work with a sample data set.
We'll introduce you to pandas, an open source library, and use it to load, manipulate, analyze, and visualize interesting data sets. Then we'll introduce you to another open source library, scikit-learn, and use some of its machine learning algorithms to build smart models and make interesting predictions.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
"A picture is worth a thousand words". We are all familiar with this expression. It is especially applicable when trying to explain the information obtained from the analysis of ever larger data sets. Data visualization plays an essential role in representing data on both a small and large scale.
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an accessible and thought-provoking way. Learning to take advantage of a software tool to visualize data will also allow you to extract insights, better understand the data, and make more effective decisions.
The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present it in a way that makes sense to people. Several techniques have been developed to present data visually, but in this course we will use several Python data visualization libraries, namely Matplotlib, Seaborn, and Folium. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to qualifying materials and a certificate.
In this course, you will apply various data analysis skills and techniques that you have learned as part of previous courses. of the IBM Data Analyst Professional Certificate. She will take on the role of an Associate Data Analyst who has recently joined the organization and be presented with a business challenge that requires data analysis to be performed on real-world data sets.
You will perform the tasks of collecting data from multiple sources, performing exploratory data analysis, data wrangling and preparation, statistical analysis and data mining, creating graphs and diagrams to visualize data, and building an interactive dashboard. The project will culminate with the presentation of its data analysis report, with an executive summary for the different stakeholders of the organization. You will be evaluated both on your work for the various stages of the data analysis process, and on the final product. This project is a great opportunity to showcase your data analysis skills and demonstrate your competence to prospective employers.
With a Coursera Professional Certificate you could start a new career or change your current career. Today's world is demanding skills and knowledge in technologies that more and more companies need. Learn at your own pace, when and where you want. In a period of less than a year you could acquire a professional certificate, which added to your current profession, could give you substantial added value to your work experience and attract the attention of "head hunters".
The most prestigious universities and the most relevant companies in the world offer professional certificates in alliance with Coursera
Professional certificates are the best way to receive top quality education in the world, at unique values.
Each study offers certification options highly valued by recruiters, or prepare you for official industry certification.
Professional certificates are in-depth studies in high-demand technology skills that you can earn in about 6-10 months.
Coursera offers courses from over 200 leading universities and companies to deliver online learning around the world. With a Coursera Plus subscription, you get unlimited access to over 90% of all courses, and the most popular professional certificates and specializations on Coursera.
Data science, business and personal development. You can enroll in multiple courses at once, earn unlimited certificates, and learn in-demand job skills to start, grow, and even change careers.
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IBM offers a wide range of consulting and technology services; a broad portfolio of middleware for collaboration, predictive analytics, software development, and systems management; and the most advanced servers and supercomputers in the world. Using its R&D, technology and business consulting expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM spends more than $6 billion a year on R&D, and just completed its 5st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 9 Nobel Laureates, 5 US National Medals of Technology, 6 US National Medals of Science, 10 Turing Awards and XNUMX inductees of the US Inventors Hall of Fame
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