What you will learn
- Understand Python language basics and apply to data science
- Practice iterative data science using Jupyter notebooks on IBM Cloud
- Analyze data using Python libraries like pandas and numpy
- Create stunning data visualizations with matplotlib, folium and seaborn
- Build machine learning models using scipy and scikitlearn
- Demonstrate proficiency in solving real life data science problems
Data is at the heart of our digital economy and Data Science has been ranked as the hottest profession of the 21st century. This 5 course Data Science with Python Professional Certificate program is aimed at preparing you for a career in Data Science and Machine Learning.
You will start by learning Python, the most popular language for Data Science. You will then develop skills for Data Analysis and Data Visualization and also get a practical introduction in Machine Learning. Finally you will apply and demonstrate your knowledge of Data Science and Machine Learning with a Capstone Project involving a real life business problem.
Taught by experts, the focus in this program is on hands-on learning and job readiness. As such you will work with real datasets and will be given no-charge access to tools like Jupyter notebooks in the IBM Cloud. You will utilize popular Python toolkits and libraries such as pandas, numpy, matplotlib, seaborn, folium, scipy, scikitlearn, etc.
Start developing data and analytical skills today and launch your career in Data Science, whether you are new to the job market or already in the workforce and looking to upskill yourself. No prior computer programming experience required.
Courses in this program
IBM's Python Data Science Professional Certificate
- 2–5 hours per week, for 1 weeks
This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own!
- 2–4 hours per week, for 5 weeks
In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!
- 2–4 hours per week, for 5 weeks
Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general.
- 4–6 hours per week, for 5 weeks
Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning.
- 3–4 hours per week, for 6 weeks
Create a project that you can use to showcase your Data Science skills to prospective employers. Apply various data science and machine learning techniques to analyze and visualize a data set involving a real life business scenario and build a predictive model.
- Over 2.5 million jobs in data science and related professions (Burning Glass)
- Python most popular language for data science (KDnuggets)
- Data Science and Analytics professionals have average starting salary of over $80,000 in the US
Meet your instructors
The shortage of skills in Data Science is a wonderful opportunity for anyone looking to enter a hot area of the job market. When we hire data scientists we highly value hands-on practical skills, especially with Python. This five course program is a great way to upgrade your skill set with an applied focus on Data Science and Machine Learning.
Unfortunately, learners from one or more of the following countries or regions will not be able to register for this program: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this program in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.