Data Science Foundations
Offered By: IBM via edX
Course Description
Overview
Data science and machine learning skills continue to be in highest demand across industries, and the need for data practitioners is booming. Upon completing this Professional Certificate program, you will be armed with the basics to jump start your career in data science and machine learning.
It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. Anyone with some computer skills and a passion for self-learning can succeed as we start small and build up to more complex problems and topics.
When you are ready you can build up to more complex topics in our full 9-course Data Science Professional Certificate program which covers a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, machine learning, and a capstone project.
With the tremendous need for data science and data analyst professionals in the market today, this program will kick-start your path in data science and arm you with the fundamentals of Data Science so that you have the confidence to take the plunge and start your data science career today.
Syllabus
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.
Courses
-
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.
-
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.
-
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.
Taught by
Maureen McElaney, Rav Ahuja, Alex Aklson, Romeo Kienzler and Svetlana Levitan
Tags
Related Courses
Data AnalysisJohns Hopkins University via Coursera Computing for Data Analysis
Johns Hopkins University via Coursera Scientific Computing
University of Washington via Coursera Introduction to Data Science
University of Washington via Coursera Web Intelligence and Big Data
Indian Institute of Technology Delhi via Coursera