Python Data Science

IBM via edX Professional Certificate

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Provider

edX Professional Certificate
Pricing

$574.00
Languages

English
Certificate

Certificate Available
Duration & workload

25 weeks, 3-5 hours a week

Found in

Overview

Data is at the heart of our digital economy and data science has been ranked as the hottest profession of the 21st century. Whether you are new to the job market or already in the workforce and looking to upskill yourself, this five course Data Science with Python Professional Certificate program is aimed at preparing you for a career in data science and machine learning. No prior computer programming experience required!

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.

This program is taught by experts and focused 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, and more.

Start developing data and analytical skills today and launch your career in data science!

Syllabus

Courses under this program:
Course 1: Python Basics for Data Science

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!

Course 2: Python for Data Science Project

This mini-course is intended for you to demonstrate foundational Python skills for working with data.

Course 3: Analyzing Data with Python

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!

Course 4: Visualizing Data with Python

Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general.

Course 5: Machine Learning with Python: A Practical Introduction

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.

Course 6: Data Science and Machine Learning Capstone Project

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.

Courses

4 reviews
3 weeks, 4-10 hours a week, 4-10 hours a week
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Please Note: Learners who successfully complete this IBM course can earn a skill badge —a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

Kickstart your learning of Python for data science, as well as programming in general with this introduction to Python course. This beginner-friendly Python course will quickly take you from zero to programming in Python in a matter of hours and give you a taste of how to start working with data in Python. ~~~~

Upon its completion, you'll be able to write your own Python scripts and perform basic hands-on data analysis using our Jupyter-based lab environment. If you want to learn Python from scratch, this course is for you.

You can start creating your own data science projects and collaborating with other data scientists using IBM Watson Studio. When you sign up, you will receive free access to Watson Studio. Start now and take advantage of this platform and learn the basics of programming, machine learning, and data visualization with this introductory course.
1 review
5 weeks, 4-6 hours a week, 4-6 hours a week
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Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

This Machine Learning with Python course dives into the basics of machine learning using Python, an approachable and well-known programming language. You'll learn about supervised vs. unsupervised learning, look into how statistical modeling relates to machine learning, and do a comparison of each.

We'll explore many popular algorithms including Classification, Regression, Clustering, and Dimensional Reduction and popular models such as Train/Test Split, Root Mean Squared Error (RMSE), and Random Forests. Along the way, you’ll look at real-life examples of machine learning and see how it affects society in ways you may not have guessed!

Most importantly, you will transform your theoretical knowledge into practical skill using hands-on labs. Get ready to do more learning than your machine!

We'll explore many popular algorithms including Classification, Regression, Clustering, and Dimensional Reduction and popular models such asTrain/Test Split, Root Mean Squared Error and Random Forests.

Mostimportantly, you will transform your theoretical knowledge into practical skill using hands-on labs. Get ready to do more learning than your machine!
2 reviews
5 weeks, 2-4 hours a week, 2-4 hours a week
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Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

"A picture is worth a thousand words." We are all familiar with this expression. It especially applies when trying to explain the insights 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.

In this course, you will learn how to leverage a software tool to visualize data that will also enable you to extract information, better understand the data, and make more effective decisions.

When you sign up for this course, you get free access to IBM Watson Studio. In Watson Studio, you’ll be able to start creating your own data science projects and collaborating with other data scientists. Start now and take advantage of everything this platform has to offer!
4 reviews
5 weeks, 2-4 hours a week, 2-4 hours a week
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Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

LEARN TO ANALYZE DATA WITH PYTHON

Learn how to analyze data using Python in this introductory course. You will go from understanding the basics of Python to exploring many different types of data through lecture, hands-on labs, and assignments. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!
0 reviews
6 weeks, 3-4 hours a week, 3-4 hours a week
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Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

Now that you've taken several courses on data science and machine learning, it’s time to put your learning to work on a data problem involving a real life scenario. Employers really care about how well you can apply your knowledge and skills to solve real world problems, and the work you do in this capstone project will make you stand out in the job market.

In this capstone project, you’ll explore data sets in New York’s 311 system, which is used by New Yorkers to report complaints for the non-emergency problems they face. Upon being reported, various agencies in New York get assigned to resolve these problems. The data related to these complaints is available in the New York City Open Dataset. On investigation, one can see that in the last few years the 311 complaints coming to the Department of Housing Preservation and Development in New York City have increased significantly.

Your task is to find out the answers to some of the questions that would help the Department of Housing Preservation and Development in New York City effectively tackle the 311 complaints coming to them. You will need to use the techniques you learned in your previous Python, data science, and machine learning courses, including data ingestion, data exploration, data visualization, feature engineering, probabilistic modeling, model validation, and more.

By the end of this course, you will have used real world data science tools to create a showcase project and demonstrate to employers that you are job ready and a worthy candidate in the field of data science.