IBM Data Analyst

Syllabus

Courses

• Databases and SQL for Data Science with Python

  1 review

  6 weeks long, 20 hours worth of material

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  Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting 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 foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment.
  
  The emphasis in this course is on hands-on and practical learning . As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs you will practice building and running 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 at no-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 only $39 USD per month for access to graded materials and a certificate.

• Data Analysis with Python

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  6 weeks long, 14 hours worth of material

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  Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will 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 Datasets
  2) Cleaning the Data
  3) Data frame manipulation
  4) Summarizing the Data
  5) Building machine learning Regression models
  6) Building data pipelines
  
  Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts:
  
  Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.
  
  If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
  
  LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

• Data Visualization with Python

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  1 week long

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  Visualizing data is used by virtually every discipline these days. It is used for analyzing web traffic to determine peak server load, growth and death rate of populations for biological analysis, analyzing weather patterns over time, stock market trends, and so on. Simply put, Data Visualization brings meaning to numbers that help people understand it. Seeing the data change can draw attention to trends and spikes that may otherwise go unnoticed. Python is an open-source (free) programming language has libraries that can be used to read and make useful graphics to present the data.
  
  In this course, you will create an application that reads data from CSV files. You will learn how to visualize the data using various techniques using existing Python libraries.
  
  
  Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

• Python for Data Science, AI & Development

  2 reviews

  5 weeks long, 20 hours worth of material

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  Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.
  
  This course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn Python fundamentals, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a final project to demonstrate your new skills.
  
  By the end of this course, you’ll feel comfortable creating basic programs, working with data, and solving real-world problems in Python. You’ll gain a strong foundation for more advanced learning in the field, and develop skills to help advance your career.
  
  This course can be applied to multiple Specialization or Professional Certificate programs. Completing this course will count towards 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 Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing your expertise in the field.

• Excel Basics for Data Analysis

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  5 weeks long, 12 hours worth of material

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  This course is designed to provide you with basic working knowledge for using Excel spreadsheets for Data Analysis. It covers some of the first steps for working with spreadsheets and their usage in the process of analyzing data. It includes plenty of videos, demos, and examples for you to learn, followed by step-by-step instructions for you to apply and practice on a live spreadsheet.
  
  Excel is an essential tool for working with data - whether for business, marketing, data analytics, or research. This course is suitable for those aspiring to take up Data Analysis or Data Science as a profession, as well as those who just want to use Excel for data analysis in their own domains. You will gain valuable experience in cleansing and wrangling data using functions and then analyze your data using techniques like filtering, sorting and creating pivot tables.
  
  This course starts with an introduction to spreadsheets like Microsoft Excel and Google Sheets and loading data from multiple formats. With this introduction you will then learn to perform some basic level data wrangling and cleansing tasks and continue to expand your knowledge of analyzing data through the use of filtering, sorting, and using pivot tables within the spreadsheet. By performing these tasks throughout the course, it will give you an understanding of how spreadsheets can be used as a data analysis tool and understand its limitations.
  
  There is a strong focus on practice and applied learning in this course. With each lab, you will gain hands-on experience in manipulating data and begin to understand the important role of spreadsheets. Clean and analyze your data faster by understanding functions in the formatting of data. You will then convert your data to a pivot table and learn its features to make your data organized and readable. The final project enables you to show off your newly acquired data analysis skills. By the end of this course you will have worked with several data sets and spreadsheets and demonstrated the basics of cleaning and analyzing data all without having to learn any code.
  
  Getting started with Excel is made easy in this course. It does not require any prior experience with spreadsheets or coding. Nor does it require downloads or installation of any software. All you need is a device with a modern web browser, and 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 follow along quite easily as well.

• Introduction to Data Analytics

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  5 weeks long, 29 hours worth of material

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  This course equips you with a practical understanding and a framework to guide the execution of basic analytics tasks such as pulling, cleaning, manipulating and analyzing data by introducing you to the OSEMN cycle for analytics projects. You’ll learn to perform data analytics tasks using spreadsheet and SQL queries. You will also be introduced to using the Python programming language to manipulate datasets as an alternative to spreadsheets. You will learn foundational programming concepts and how they apply to marketing. You will also learn how to use Tableau to create data visualizations and dashboards.
  
  By the end of this course, you will be able to:
  • State business goals, KPIs and associated metrics
  • Apply a Data Analysis Process: OSEMN
  • Identify and define the relevant data to be collected for different marketing related questions
  • Compare and contrast the different formats and use cases of different kinds of data
  • Identify gaps in data collected and describe the strengths and weaknesses in the available data
  • Demonstrate basic proficiency in Python with variables, control flow, loops, and basic data structures
  • Sort, query and structure data in spreadsheets and with Python libraries
  • Write basic SQL statements to select, group and filter data
  • Visualize data patterns and trends with spreadsheets
  • Utilize Tableau to visualize data patterns and trends
  
  This course is designed for people who want to learn the basics of data analytics including using spreadsheets and Python to sort and structure data and using Tableau to visualize data patterns.
  
  Learners don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Learners also need access to a computer with strong internet connection. Ideally learners have already completed course 1 (Marketing Analytics Foundation) in this program.

• Data Visualization and Dashboards with Excel and Cognos

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  4 weeks long, 9 hours worth of material

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  This course covers some of the first steps in the development of data visualizations using spreadsheets and dashboards. Begin the process of telling a story with your data by creating the many types of charts that are available in spreadsheets like Excel. Explore the different tools of a spreadsheet, such as the important pivot function and the ability to create dashboards and learn how each one has its own unique property to transform your data. Continue to gain valuable experience by becoming familiar with the popular analytics tool - IBM Cognos Analytics - to create interactive dashboards.
  
  By completing this course, you will have a basic understanding of using spreadsheets as a data visualization tool. You will gain the ability to effectively create data visualizations, such as charts or graphs, and will begin to see how they play a key role in communicating your data analysis findings. All of this can be accomplished 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 dashboarding tools used by a data analyst, design and create a dashboard in a cloud platform, and begin to elevate your confidence level in creating intermediate level data visualizations.
  
  Throughout this course you will encounter numerous hands-on labs and a final project. With each lab, gain hands-on experience with creating basic and advanced charts, then continue through the course and begin creating dashboards with spreadsheets and IBM Cognos Analytics. You will then end 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 prospective employers.
  
  This course does not require any prior data analysis, or computer science experience. All you need to get started is basic computer literacy, high school level math, access to a modern web browser such as Chrome or Firefox, the ability to create a Microsoft account to access Excel for the Web, and a basic understanding of Excel spreadsheets.

• IBM Data Analyst Capstone Project

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  6 weeks long, 14 hours worth of material

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  In this course you will apply various Data Analytics skills and techniques that you have learned as part of the previous courses in the IBM Data Analyst Professional Certificate. You will assume 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 datasets.
  
  You will undertake the tasks of collecting data from multiple sources, performing exploratory data analysis, data wrangling and preparation, statistical analysis and mining the data, creating charts and plots to visualize data, and building an interactive dashboard. The project will culminate with a presentation of your data analysis report, with an executive summary for the various stakeholders in the organization. You will be assessed on both your work for the various stages in the Data Analysis process, as well as the final deliverable.
  
  This project is a great opportunity to showcase your Data Analytics skills, and demonstrate your proficiency to potential employers.