10 Best DataCamp Courses in 2021!

Learn how to deal with massive amounts of data and make important business decisions. With these 10 Best Courses from DataCamp, learn Data Science from scratch.

10 Best DataCamp Courses in 2021!

Data science is an area that uses advanced analytical techniques and scientific principles to extract valuable information from data for business decisions, strategic planning, and other purposes. Data science enables real-time analysis of data as it is produced and read.

The benefits of real-time analysis include faster decision-making and increased business agility. The popularity of Data Science increases every year as companies begin to use data science techniques to grow their business and increase customer satisfaction.

DataCamp is an excellent and popular online learning platform to improve your skills for the future of data science. They offer courses in data science, Python, SQL, R, programming, big data, machine learning, deep learning, and applied finance. Their courses are great for anyone starting their data analytics career.

As the name suggests, DataCamp focuses on data programming and management. They offer subscriptions to their courses for just $13 a month. These courses are affordable and a worthwhile investment if you want to learn how to use data.

DataCamp lets you choose from a variety of online courses as with other online learning platforms to help you develop your skills in fields such as data science and analytics.

As Data Science seems to be near you, read on for some of the best Data Science Courses on offer.

Top DataCamp Courses List

  1. Introduction to Python

  2. Introduction to R

  3. Introduction to SQL

  4. Data Manipulation with pandas

  5. Introduction to the Tidyverse

  6. Data Science for Everyone

  7. Introduction to Data Visualization with Matplotlib

  8. Joining Data in SQL

  9. Supervised Learning with scikit-learn

  10. Data Analysis in Spreadsheets

1. Introduction to Python

Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.

Course rating: 3,669,978 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will:

  • Understand the basic concepts of Python.
  • Learn how to use Python interactively and by using a script.
  • Create your first variables and acquaint yourself with Python's basic data types.
  • Learn to store, access, and manipulate data in lists: the first step toward efficiently working with huge amounts of data.

Unlike other Python tutorials, this course focuses on Python specifically for data science. In this Python Introductory course, you will learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses.

In addition, you will learn how to use functions, methods, and packages to efficiently leverage the code that brilliant Python developers have written. You will also learn to work with powerful tools in the NumPy array and get started with data exploration. Start DataCamp’s online Python curriculum now.

2. Introduction to R

Learn R Programming from scratch. Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

Course rating: 2,078,689 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will learn:

  • How to use the console as a calculator and how to assign variables.
  • The basic data types in R Programming.
  • Analyzing your gambling results using vectors.
  • How to create vectors in R, name them, select elements from them, and compare different vectors.
  • Creating and working with matrices.
  • Creating a data frame, selecting interesting parts of a data frame, and ordering a data frame according to certain variables.

With this Introduction to R course, you will master the basics of this widely used open-source language, including factors, lists, and data frames. Here, you will learn how to understand the basic data types in R and how you can create & analyze your gambling results using vectors in R.

Plus, categorical data is stored in factors in R. These factors are very important in data analysis, so you will learn how to create, subset, and compare them now. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis.

3. Introduction to SQL

Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.

Course rating: 1,132,710 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will:

  • Learn syntax in SQL shared by many types of databases, such as PostgreSQL, MySQL, SQL Server, and Oracle.
  • Learn working with Relational Databases and their structure.
  • Understand Relational Databases using Database Lingo.
  • Begin an analysis using simple SQL commands to select and summarize columns from database tables.
  • Filter tables for rows satisfying some criteria of interest.
  • Use aggregate functions to summarize data and gain useful insights.

Initially, you will learn everything you need to learn about Relational Databases then you will learn how to use basic comparison operators, combine multiple criteria, match patterns in text, and much more.

The course teaches you how to use aggregate functions to summarize data and gain useful insights. You'll also learn about arithmetic in SQL and how to use aliases to make your results more readable. Plus, it provides a brief introduction to sorting and grouping your results.

This course teaches you everything you need to know to begin working with databases today!

4. Data Manipulation with pandas

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.

Course rating: 135,293 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will learn:

  • How to inspect DataFrames.
  • Performing fundamental manipulations, including sorting rows, subsetting, and adding new columns.
  • Calculating summary statistics on DataFrame columns.
  • Grouped summary statistics and pivot tables.
  • How to visualize the contents of your DataFrames, handle missing data values, and import data from and export data to CSV files.

In addition to data manipulation and analysis, Pandas is the most popular Python library. You will learn how to manipulate DataFrames as you extract, filter, and transform real-world datasets to analyze them.

With Pandas, you'll learn all the core data science concepts. As you analyze real-world data such as Walmart sales figures and global temperatures, you will use pandas to add to the power of Python to import, clean, calculate statistics, and create visualizations!

5. Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the Tidyverse, a powerful and popular collection of data science tools within R.

Course rating: 206,895 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will learn:

  • How to filter a table for particular observations.
  • Arranging the observations in the desired order, and mutate to add or change a column.
  • Essential skills of data visualization using the ggplot2 package.
  • How the dplyr and ggplot2 packages work closely together to create informative graphs.
  • Using the group by and summarize verbs, which collapse large datasets into manageable summaries.

The Tidyverse is a powerful set of tools that provide an introduction to the programming language R. Using ggplot2 and dplyr, you'll become familiar with the intertwined processes of data manipulation and visualization.

You will learn how to manipulate data by filtering, sorting, and summarizing a real dataset of historical country data to answer exploratory questions. This data will then be transformed into line plots, bar plots, histograms, and more with the ggplot2 package.

You'll feel the power of Tidyverse tools and get a feel for exploratory data analysis. For those with no prior knowledge of R and those interested in performing data analysis, this is an excellent introduction.

6. Data Science for Everyone

An introduction to data science with no coding involved.

Course rating: 170,305 total enrollments

Duration: 2 h

Certificate: Certificate on completion

In this course, you will:

  • Learn what data science is.
  • Cover the data science workflow and how data science is applied to real-world problems.
  • Understand different roles within the data science field.
  • Learn about the different data sources you can draw from.
  • Diagnose problems in your data, deal with missing values and outliers.
  • Learn about visualization, another essential tool to both explore your data and convey your findings.

What is data science, why is it so popular, and why was it named the "sexiest job of the 21st century" by the Harvard Business Review? This non-technical course will introduce you to everything you were too afraid to ask about this fast-growing and exciting field, without requiring you to write a single line of code.

During the course, you'll experience hands-on exercises covering topics such as A/B testing, time series analysis, and machine learning, along with learning how data scientists analyze real-world data to extract knowledge and insights. Don't let the buzzwords deter you.

Get started learning, gain skills in this highly in-demand field, and discover why data science is for you!

7. Introduction to Data Visualization with Matplotlib

Learn how to create, customize, and share data visualizations using Matplotlib.

Course rating: 77,774 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will:

  • Understand Matplotlib visualization library and how to use it with data.
  • Visualizing how Time series data helps clarify trends and illuminates relationships between data.
  • Compare data in a quantitative manner.
  • Learn how to share your visualizations with others.
  • Save your figures as files.

Using plots and figures to visualize data reveals underlying patterns and provides insights. In addition to helping you communicate your data to others, good visualizations are useful for data analysts and other consumers of the data.

This course will teach you how to use Matplotlib, a powerful Python data visualization library. Matplotlib provides the building blocks for creating rich visualizations of many different kinds of data.

Throughout the course, you will learn how to design and automate visualizations for different types of data as well as how to share them.

8. Joining Data in SQL

Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.

Course rating: 232,735 total enrollments

Duration: 5 h

Certificate: Certificate on completion

In this course, you will:

  • Learn the concept of joining tables.
  • Use the case statement to split up a field into different categories.
  • Come to grips with different kinds of outer joins.
  • Gain further insights into your data through left joins, right joins, and full joins.
  • Learn more about set theory using Venn diagrams.

During this course, you'll learn about the power of joining tables while exploring interesting characteristics of countries and their cities around the world.

The course covers inner and outer joins, self joins, semi joins, anti joins and cross joins--essential tools in any PostgreSQL wizard's toolbox. You'll never have to fear set theory again after learning all about unions, intersections, and except clauses through easy-to-understand diagrams and examples.

Finally, you will learn about the challenging topic of subqueries. Using Venn diagrams and other illustrations, you will be able to easily grasp these ideas.

9. Supervised Learning with scikit-learn

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

Course rating: 266,349 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will:

  • Understand classification problems and learn how to solve them using supervised learning techniques.
  • Classify the party affiliation of United States congressmen based on their voting records.
  • Learn about fundamental concepts in regression.
  • Apply fundamental concepts to predict the life expectancy in a given country using Gapminder data.
  • Optimize your classification and regression models using hyperparameter tuning.

Machine learning is the process of teaching computers to learn from existing data to make predictions about new data: Will a tumor be benign or malignant? Will your customers switch to another vendor? Is an email spam?

The goal of this course is to teach you how to perform supervised learning with Python, an essential part of machine learning. Using real-world datasets, you'll learn how to build predictive models, tune their parameters, and determine how well they will perform with unseen data.

The course also includes scikit-learn, one of Python's most popular machine learning libraries.

10. Data Analysis in Spreadsheets

Learn how to analyze data with spreadsheets using functions such as SUM(), AVERAGE(), and VLOOKUP().

Course rating: 266,349 total enrollments

Duration: 4 h

Certificate: Certificate on completion

In this course, you will:

  • Use these Google Sheets: predefined functions to solve complex problems without having to worry about specific calculations.
  • Cover a lot of predefined functions, including functions for numbers, functions for strings, and functions for dates.
  • Master more advanced functions like IF() and VLOOKUP().

You will learn more about some of Google Sheets' core features in this course. In addition to SUM() and AVERAGE(), you will discuss VLOOKUP() and other predefined functions.

These techniques will be used to analyze your grades at school, to analyze performance statistics at a company, to track sales over time, and to review some geographic data about countries around the world.


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