Applied Data Science

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement.

This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python Specialization. This capstone project course will give you the chance to practice the work that data scientists do in real life when working with datasets. In this course you will assume the role of a Data Scientist working for a startup intending to compete with SpaceX, and in the process follow the Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting your results to stakeholders. You will be tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. With the help of your Data Science findings and models, the competing startup you have been hired by can make more informed bids against SpaceX for a rocket launch. In this course, there will not be much new learning, instead you’ll focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your data science and machine learning portfolio to showcase to employers.

Go from zero to working with real data in Python. No programming experience required. Data skills are some of the most in-demand skills in the job market. The U.S. Bureau of Labor Statistics projects data scientist employment to grow 34% from 2024 to 2034, much faster than average, with a median annual wage of $112,590.¹ Python is the language behind that work, and this course is where you start. This IBM course takes you from your first line of code to the skills data teams use every day. You'll start with Python basics, then build up through data structures, logic, functions, error handling, and object-oriented programming. From there, you'll work with real data using NumPy and Pandas, the industry-standard libraries for data analysis and AI, and learn to collect it from the web using REST APIs and web scraping with BeautifulSoup. You'll learn by doing. Across five modules, you'll complete more than 25 hands-on labs and practice projects in Jupyter Notebooks, the same environment professional data scientists use, with nothing to install or set up. By the end, you'll be able to write programs, clean and analyze datasets, pull data from live sources, and automate repetitive tasks, and you'll have practical work to point to in interviews. Whether you're aiming for a career in data science, data analytics, software development, data engineering, AI, or DevOps, or you want to add Python to the skills you already have, this course gives you the foundation to build on. Skills you'll gain include: - Writing Python programs using variables, data structures, loops, functions, and classes - Reading, writing, and processing data in CSV, JSON, and text formats - Analyzing and manipulating data with Pandas and NumPy - Collecting data from websites and services using REST APIs and web scraping - Working in Jupyter Notebooks to develop and document your code - Automating real-world tasks with Python scripts Join 1.5 million+ learners (4.6 stars from 43,000+ reviews, and 95% of learners liked this course). Finish with a shareable certificate you can add to your LinkedIn profile, resume, or CV. ¹ U.S. Bureau of Labor Statistics, Occupational Outlook Handbook: Data Scientists. Median wage as of May 2024; projected growth 2024 to 2034. This course builds foundational Python skills and is a first step toward data roles, not a guarantee of employment or salary.

This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course primarily involves completing a project in which you will assume the role of a Data Scientist or a Data Analyst and be provided with a real-world data set and a real-world inspired scenario to identify patterns and trends. You will perform specific data science and data analytics tasks such as extracting data, web scraping, visualizing data and creating a dashboard. This project will showcase your proficiency with Python and using libraries such as Pandas and Beautiful Soup within a Jupyter Notebook. 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 pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much instructional content. It is intended for you to apply prior Python knowledge.