Booz Allen Hamilton reports that organizations experienced a 17-49% increase in productivity when they increased data usability by 10%. Given the positive impact that professionals can have on their organizations' performance by employing data science, Cognitir created Introduction to Data Science to help both business and nonbusiness professionals acquire foundational data science skills that will help them analyze data better.
In this course, participants will learn the Python programming language and how to use it to execute relevant data science techniques on complex data. In addition, participants will learn how to correctly evaluate the results of different data science methods with the aim of being able to draw meaningful business conclusions from them. After this course, professionals will become better, more data-driven decision makers.
Attendees can use either a Mac or Windows computer for this course.
An overview of foundational data science and machine learning methods and how they can be used to solve real-world problems
All of our classes use relevant, Python-based exercises to help students apply theory to practice. Students write their own Python code during the workshop.
Understanding of the advantages of data science and specific analytical methods and the kinds of questions they can help answer
Understanding of effective data visualization techniques, how to execute data visualization tasks in Python, and how to communicate results to key stakeholders
Participants will have opportunities to discuss current data science topics with other attendees & their Cognitir instructor and brainstorm practical strategies to improve decision making
All Cognitir participants receive course notes, a certificate of completion, instructions on how to add the course to their LinkedIn profiles, and post-seminar email support
This course is relevant for both business and nonbusiness professionals who analyze data on a regular basis. The business professionals who would most benefit from taking our course include: finance, marketing/advertising, operations, and strategy professionals in corporations as well as management consultants. Nonbusiness professionals who would benefit from taking this course include professionals in: law, medicine, politics, public health, public policy, and sports analytics.
No prior programming experience required.
Not sure if this is the right course for you? Contact us.
No, you do not need any prior programming experience for this course. However, we will provide introductory material to participants ahead of the course if they want to prepare a bit before. In the past, we have found that participants with prior experience can also still benefit from the course by tackling some of the more advanced exercises we offer. Additionally, they find the material an excellent refresher for concepts that they learned a while ago but have not applied on the job for one reason or another.How is this course different from Data Science for Managers?
This course focuses more on the hands-on technical aspects of data science. Attendees will build computer programs that execute different data science tasks. Data Science For Managers is not programming-based. The course discusses data science as a strategic tool in problem solving and is meant for individuals managing data science, technical, or business intelligence teams.Do I have the right laptop for this course?
You will need a PC (Windows Vista or newer), Mac (OS X 10.7 or newer), or Linux (Ubuntu, RedHat and others; CentOS 5+). Please contact us if you are planning to use a different setup for this course.Do I need to install software prior to the class?
Yes, you will need to download and install free Python software on your laptop. In case you are planning on using a company laptop, please make sure that you have the necessary rights to install the tools. We will send out detailed information on the download and installation procedures a few days before the course starts.
Visit our FAQs to see commonly asked questions from participants about data science.