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LinkedIn Learning

Become a Data Scientist

via LinkedIn Learning Path

Overview

Prepare for a new career with $100 off Coursera Plus
Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.
Whether you're working in IT or simply have an interest in entering the exciting field, this learning path will support you in developing a career in data science. Learn about the fundamental stages of data science work, from Statistics and Systems Engineering to Data Mining and Machine Learning.
  • Build a solid foundational understanding of statistics, which is necessary for any data science-related field.
  • Discover the many categories of job specialization within Data Science.
  • Learn how to source, explore, and communicate with data through graphs and statistics.

Syllabus

Courses under this program:
Course 1: A Day In The Life of a Data Scientist
-Follow along with one day in the life of real data scientists working on real projects. Get on-the-job insights to help prepare you to tackle the next challenge or choose your next data science role.

Course 2: The Non-Technical Skills of Effective Data Scientists
-Learn the nontechnical skills that effective data scientists must nurture to convert their first job into a successful, lifelong career.

Course 3: Data Science & Analytics Career Paths & Certifications: First Steps
-Learn about the jobs and most valuable certifications available in big data, data analytics, and data science.

Course 4: Data Science Foundations: Fundamentals (2019)
-Get a basic introduction to the careers, tools, and techniques of modern data science.

Course 5: Statistics Foundations: The Basics
-Learn to understand your data using basics of statistics, such as defining the middle, mean, and median of your data set; measuring the standard deviation; and finding outliers.

Course 6: Statistics Foundations: Probability
-Learn to understand your data in beginner-friendly lessons, using probability. Topics include permutations, percentiles, how to use probability trees, and much more.

Course 7: Data Visualization: Storytelling
-Learn the keys to telling a story with data from data visualization expert Bill Shander.

Course 8: Big Data in the Age of AI
-Explore big data and how it works. Learn about big data's relationship to AI, data science, social media, and the Internet of Things (IoT).

Course 9: Learning Data Governance
-Understand why data governance is an essential part of helping every organization succeed in the era of big data and data science

Course 10: Data Fluency: Exploring and Describing Data (2019)
-Learn how anyone, in any industry, can speak the language of data analysis. Find out how to prepare data, explore it visually, and describe it using statistical methods.

Course 11: Lessons from Data Scientists
-Get advice and real-world lessons from practicing data scientists: from how to get a job to mastering your skills to growing in your role.

Course 12: Side Hustle Strategies for Data Science and Analytics Experts
-Diversify your career prospects by integrating a side hustle with your existing responsibilities. Learn how to leverage your data science and analytics skills to work for yourself.

Courses

Taught by

Lacey Westphal, Ph.D., Keith McCormick, Jungwoo Ryoo, Barton Poulson, Eddie Davila, Bill Shander and Jonathan Reichental, Ph.D.

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