About this Course
Get hands-on skills for a career in data science. Learn Python, analyze and visualize data. Apply your skills to data science and machine learning. This action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real-world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this applied data science specialization is for you.
The Applied Data Science Specialization is a 4-course program that will give you the tools you need to analyze data and make data-driven business decisions leveraging computer science and statistical analysis. You will learn Python–no prior programming knowledge necessary–and discover methods of data analysis and data visualization. You’ll utilize tools used by real data scientists like Numpy and Pandas, practice predictive modeling and model selection, and learn how to tell a compelling story with data to drive decision making.
Through guided lectures, labs, and projects in the IBM Cloud, you’ll get hands-on experience tackling interesting data problems from start to finish. Take this Specialization to solidify your Python and data science skills before diving deeper into big data, AI, and deep learning.
In addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing you as a specialist in applied data science.
This Specialization can also be applied toward the IBM Data Science Professional Certificate.
What you will learn from this course?
- Develop an understanding of Python fundamentals.
- Gain practical Python skills and apply them to data analysis.
- Communicate data insights effectively through data visualizations.
- Create a project demonstrating your understanding of applied data science techniques and tools.
There are 5 Courses in this Specialization
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.
This mini-course is intended to for you to demonstrate foundational Python skills for working with data. The completion of this course involves working on a hands-on project where you will develop a simple dashboard using Python.
This course is part of the IBM Data Science Professional Certificate and the IBM Data Analytics Professional Certificate.
Pre-Requisite for Python Project for Data Science
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.
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!
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.
“A picture is worth a thousand words”. We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, 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 that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium.
Project for Applied Data Science
Complete hands-on labs and projects in the IBM Cloud by applying your newly acquired skills and knowledge throughout the Specialization. Projects include creating a random album generator, building a machine learning model, and analyzing geospatial data.
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- 3+ Months
- Paid Course (Paid certificate)
- Artificial intelligence Data Science Data Science with 'Python'