IBM Data Science

IBM via edX Professional Certificate

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Provider

edX Professional Certificate
Pricing

$970.00
Languages

English
Certificate

Certificate Available
Duration & workload

49 weeks, 3-5 hours a week
Level

Beginner

Found in

Overview

The demand for data scientists is projected to grow 10x faster than other occupations (Source: US Bureau of Labor Statistics). This IBM Data Science Professional Certificate gives you the job-ready skills and practical experience you need to start your career in data science and machine learning. No prior computer science or programming experience is required.

Data scientists analyze and interpret complex, large datasets using data mining, machine learning, and predictive modeling techniques. They then seek to uncover patterns, trends, and insights that help businesses make informed decisions.

During this program, you’ll learn Python programming, SQL for database querying, data manipulation with Pandas and Numpy, data visualization with Matplotlib and Seaborn, and machine learning with Scikit-learn. You’ll work hands-on with data science tools like Jupyter Notebooks, RStudio, and IBM watsonx. You'll use GitHub for version control and access data sources with APIs. Plus, you’ll gain valuable practical skills through hands-on labs, course projects, and a capstone project you can put on your resume and talk about in interviews.

If you’re looking to get started in data science, this program gives you the job-ready skills you need to catch the eye of an employer. Enroll today and look forward to kickstarting a highly rewarding career.

Syllabus

Courses under this program:
Course 1: Introduction to Data Science

Learn about the world of data science first-hand from real data scientists.

Course 2: Data Science Tools

Learn about the most popular data science tools, including how to use them and what their features are.

Course 3: The Data Science Method

Learn about the methodology, practices and requirements behind data science to better understand how to problem solve with data and ensure data is relevant and properly manipulated to address a variety of real-world projects and business scenarios.

Course 4: SQL for Data Science

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field.

Course 5: 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 6: Python for Data Science Project

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

Course 7: 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 8: 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 9: 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 10: 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

6 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.
0 reviews
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.
0 reviews
7 weeks, 3-7 hours a week, 3-7 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!

Despite and influx in computing power and access to data over the last couple of decades, our ability to use data within the decision-making process is either lost or not maximized all too often. We do not have a strong grasp of the questions asked and how to apply the data correctly to resolve the issues at hand.

The purpose of this course is to share the methods, models and practices that can be applied within data science, to ensure that the data used in problem-solving is relevant and properly manipulated to address business and real-world challenges.

You will learn how to identify a problem, collect and analyze data, build a model, and understand the feedback after model deployment.

Advancing your ability to manage, decipher and analyze new and big data is vital to working in data science. By the end of this course, you will have a better understanding of the various stages and requirements of the data science method and be able to apply it to your own work.
1 review
4 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!

Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases. A working knowledge of databases and SQL is necessary to advance as a data scientist or a machine learning specialist. 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, 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.
0 reviews
7 weeks, 3-7 hours a week, 3-7 hours a week
View details

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!

In this course, you'll learn about Data Science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages they can execute, their features and limitations and how data scientists use these tools today.

With the tools hosted in the cloud, you will be able to test each tool and follow instructions to run simple code in Python or R. To complete the course, you will create a final project with a Jupyter Notebook on IBM Watson Studio on Cloud and demonstrate your proficiency in preparing a notebook, writing Markdown, and sharing your work with your peers.

This hands-on course will get you up and running with some of the latest and greatest data science tools.