Is Data Analytics Really That Hard? Tips for Rising to the Challenge
January 30, 2025
Article
This course is part of How to Use Data Specialization
Instructor: Brandon Krakowsky
Included with
Recommended experience
Beginner level
Familiarity with Python.
Recommended experience
Beginner level
Familiarity with Python.
Classifying and analyzing data.
Executing SQL queries to work with data.
Using Python and pandas library to manipulate and explore data.
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February 2025
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The ability to understand and work with data has become increasingly important in today's world, where data is ubiquitous and valuable. This course covers a range of topics, including what data is and
its different types, what big data looks like, and how companies are using it. It also explores the fields of data analysis and data science and how the two come together. To help form the field of data analytics, we'll look at the entire data analytics process and how it works, from defining the analytics problem to interpreting and presenting the results. We'll also look at some case studies, which are presented to illustrate the application of data analytics in real-world scenarios.
The ability to understand and work with data has become increasingly important in today's world, where data is ubiquitous and valuable. The first module in this course covers a range of topics, including what data is and its different types, what "big" data looks like, and how companies are using it. It also explores the fields of data analysis and data science, and how the two come together to help form the field of data analytics.
11 videos3 readings3 assignments
There are multiple ways of storing and accessing data, with a variety of deployment strategies and storage options, including databases, data warehouses, and data lakes. In week 2, we’ll look at accessing data in a database. We’ll provide some context around relational databases, and then do a deep dive into SQL, which is a query language used for accessing and updating databases.
22 videos8 readings2 assignments4 app items
Real-world problems are often hidden behind large amounts of data. Through exploratory data analysis (EDA), we can distill valuable information from data and make reliable predictions about it. In other words, Python and data analytics provide computer scientists with effective tools for understanding, processing, and utilizing real-world data. This module will take an in-depth look at how to use the powerful Python libraries pandas and NumPy to perform key tasks such as loading, querying, cleaning, summarizing, and visualizing data.
21 videos7 readings3 assignments4 app items
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
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