10 Best DataCamp Courses

The Trainee’s Corner brings you the 10 best DataCamp Courses. All courses have several chapters, and you can access the first chapter of all courses for free. DataCamp offers Standard and Premium yearly memberships, that are priced $25 and $33.25 per month respectively. After completing any course, trainees will earn a statement of accomplishment. The list below will be updated regularly with the most trending and popular courses available at DataCamp.

Python is a general-purpose programming language that is becoming very popular for data science. Companies worldwide use Python to harvest insights from their data and gain a competitive edge. Unlike other Python tutorials, this course focuses on Python specifically for data science. In this Introduction to Python course, you will learn about powerful ways to store and manipulate data, as well as helpful data science tools to begin conducting your own analyses.

 Course highlights:

  • Duration: 4 hours
  • Skills: Python, Data Science, Data Analysis

In Introduction to R course, you will master the basics of this widely used open source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis. Oracle estimated over 2 million R users worldwide in 2012, cementing R as a leading programming language in statistics and data science. Every year, the number of R users grows by about 40%, and an increasing number of organizations are using it in their day-to-day activities.

Course highlights:

  • Duration: 4 hours
  • Skills: R, Data Analysis 

The role of a data scientist is to turn raw data into actionable insights. Much of the world’s raw data—from electronic medical records to customer transaction histories—lives in organized collections of tables called relational databases. To be an effective data scientist, you must know how to wrangle and extract data from these databases using a language called SQL. This course teaches syntax in SQL shared by many types of databases, such as PostgreSQL, MySQL, SQL Server, and Oracle. This course teaches you everything you need to know to begin working with databases today.

Course highlights:

  • Duration: 4 hours
  • Skills: SQL, Databases

This intermediate course of Python will teach you how to visualize real data with Matplotlib’s functions and get acquainted with data structures such as the dictionary and the pandas DataFrame. After covering key concepts such as boolean logic, control flow, and loops in Python, you will be ready to blend together everything you have learned to solve a case study using hacker statistics.

Course highlights:

  • Duration: 4 hours
  • Skills: Python, Data Analysis

In this intermediate course of R, you will learn about conditional statements, loops, and functions to power your own R scripts. Next, make your R code more efficient and readable using the apply functions. Finally, the utilities chapter gets you up to speed with regular expressions in R, data structure manipulations, and times and dates. This course will allow you to take the next step in advancing your overall knowledge and capabilities while programming in R.

Course highlights:

  • Duration: 6 hours
  • Skills: R, Data Analysis

Data scientists spend 80% of their time cleaning and manipulating data and only 20% of their time actually analyzing it. For this reason, it is critical to become familiar with the data cleaning process and all of the tools available to you along the way. This course provides a very basic introduction to cleaning data in R using the tidyr, dplyr, and stringr packages. After taking the course you will be able to go from raw data to awesome insights as quickly and painlessly as possible.

Course highlights:

  • Duration: 4 hours
  • Skills: R, Data Cleaning

This DataCamp course extends your existing Python skills to provide a stronger foundation in data visualization in Python. You will get a broader coverage of the Matplotlib library and an overview of seaborn, a package for statistical graphics. Topics covered include; customizing graphics, plotting two-dimensional arrays (such as pseudocolor plots, contour plots, and images), statistical graphics (like visualizing distributions and regressions), and working with time series and image data.

 Course highlights:

  • Duration: 4 hours
  • Skills: Python, Data Visualization

This DataCamp course provides a comprehensive introduction on how to plot data with R’s default graphics system, base graphics. After an introduction to base graphics, we look at a number of R plotting examples, from simple graphs such as scatterplots to plotting correlation matrices. The course finishes with exercises in plot customization. This includes using R plot colors effectively and creating and saving complex plots in R.

 Course highlights:

  • Duration: 4 hours
  • Skills: R, Data Visualization

This DataCamp course is perfect for those who have a solid basis in R and statistics, but are complete beginners with machine learning. After a broad overview of the discipline’s most common techniques and applications, you will gain more insight into the assessment and training of different machine learning models. The rest of the course is dedicated to a first reconnaissance with three of the most basic machine learning tasks: classification, regression and clustering.

 Course highlights:

  • Duration: 6 hours
  • Skills: R, Machine Learning

In this DataCamp course you will learn the basics of using SQL with Python. This will be useful because databases are ubiquitous and data scientists, analysts, and engineers must interact with them constantly. The Python SQL toolkit SQLAlchemy provides an accessible and intuitive way to query, build, and write to essential databases, including SQLite, MySQL, and PostgreSQL.

 Course highlights:

  • Duration: 4 hours
  • Skills: Python, SQL, Databases

7 Best DataCamp Skill Tracks

The Trainee’s Corner brings you the 7 best DataCamp Skill Tracks. All skill tracks include several courses, and you will earn a statement of accomplishment after completing the last course. The list below will be updated regularly with the most trending and popular skill tracks available at DataCamp.

Machine Learning Fundamentals with Python Skill TrackIn this DataCamp skill track, you will learn the fundamental concepts in Machine Learning. It consists of five well-rounded courses, where you will be learning from supervised and unsupervised learning techniques to linear classifiers and deep learning fundamentals, using Python as the main programming language. 

 Skill Track highlights:

  • Includes 5 courses
  • Duration: 20 hours
  • Skills: Python, Machine Learning, Deep Learning

Data Skills for Business Skill TrackIn this DataCamp skill track, you will learn core data concepts, understand how to answer real-world questions using data, and become a more confident data-driven decision-maker within your organization. This track will help you sharpen your data skills and identify when data can be used to solve business challenges. You will learn indispensable data terminology, tools, and questions that you can ask to communicate more effectively with your analytics team. You will be introduced to statistics in spreadsheets, Python, machine learning, and AI to help you better lead your team.

Skill Track highlights:

  • Includes 4 courses
  • Duration: 16 hours
  • Skills: Data skills

Big Data with R Skill TrackIn this five courses’ DataCamp skill track, you will learn how to write scalable and efficient R code as well as ways to visualize it. R language has great ways to handle working with big data including parallel programming and interfacing with Apache Spark. You will be using tools such as trelliscopejs, ggplot2, bigmemory, iotools and much more.  

Skill Track highlights:

  • Includes 5 courses
  • Duration: 20 hours
  • Skills: Big Data, R

Importing and Cleaning Data with R Skill TrackIn this four courses’ DataCamp skill track, you will learn how to import your data from a variety of sources, including .csv, .xls, text files, and more. This will let you gain the skills you need to afterwards prepare your data for analysis, including converting data types, filling in missing values, and using fuzzy string matching. Throughout the track, you will have the chance to apply your skills to real-world data such as customer asset portfolios and restaurant reviews.  

Skill Track highlights:

  • Includes 4 courses
  • Duration: 14 hours
  • Skills: R, Data Import, Data Cleaning

Network Analysis with R Skill TrackAs networks appear in lots of important places nowadays, from public transport to Social Media, this four courses’ DataCamp skill track focus on showing how to analyze and visualize network data. You will be using tools such as tidyverse or igraph, just to name a few. The main programming language used in this skill track is R. 

Skill Track highlights:

  • Includes 4 courses
  • Duration: 16 hours
  • Skills: R, Network Analysis

Data Manipulation with Python Skill TrackIn this four courses’ DataCamp skill track you will learn how to prepare real-world data for analysis and grow your expertise as you work with multiple DataFrames using pandas, the most popular Python data science package to manipulate data. You will also gain hands-on experience of how to combine, merge, and create visualizations. At the end of the track, you will be applying your new-found data manipulation skills to analyze the impact of weather and gender on police behavior. 

Skill Track highlights:

  • Includes 4 courses
  • Duration: 16 hours
  • Skills: Python, Data Manipulation

Data Visualization with Python Skill TrackTaking this five courses’ DataCamp skill track will allow you to supercharge your data science skills using Python’s most popular and robust data visualization libraries. You will learn how to use Matplotlib, Seaborn, Bokeh, and others to create beautiful static and interactive visualizations of categorical, aggregated, and geospatial data.

Skill Track highlights:

  • Includes 5 courses
  • Duration: 20 hours
  • Skills: Python, Data Visualization

5 Best DataCamp Career Tracks

We came up with the following 5 best DataCamp Career Tracks. All DataCamp career tracks include several courses, and let you earn a statement of accomplishment after completing the last course. The list below will be updated regularly with the most trending and popular career tracks available at DataCamp.

In this career track, you will learn how the versatility of Python allows you to import, clean, manipulate, and visualize data, all integral skills for any aspiring data professional or researcher. Through interactive exercises, you will get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more. You will use real-world datasets to learn the statistical and machine learning techniques you need to train decision trees and use natural language processing (NLP). Start this track, grow your Python skills, and begin your journey to becoming a confident data scientist.

Career Track highlights:

  • Includes 23 courses
  • Duration: 88 hours
  • Skills: Python, Data Science

Data Engineer with Python career trackData Engineers lay the groundwork that makes data science possible. As many businesses are collecting a huge amount of data nowadays, Data Engineers are there to take care of data collection, ingestion, and warehousing. That is the main job of a Data Engineer, to ensure that data is stored safely and correctly. This career track assumes fundamental Python and SQL knowledge. DataCamp recommends to test you have the relevant Python knowledge, by completing a Python Programming skill assessment

Career Track highlights:

  • Includes 19 courses
  • Duration: 75 hours
  • Skills: Python, Data Engineering

Data Analyst with Python career trackIn this career track, you will learn how to import, clean, manipulate, and visualize data. Through interactive exercises, you will get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more. You’ll also gain experience of working with real-world datasets, including data from the Titanic and from Twitter’s streaming API, to grow your data manipulation and exploratory data analysis skills, before moving on to learn the SQL skills you’ll need to query data from databases and join tables. This track will definitely help you to begin your journey to becoming a confident data analyst.

Career Track highlights:

  • Includes 16 courses
  • Duration: 62 hours
  • Skills: Python, Data Analysis

Machine earning Scientist with Python career trackIn this career track, you will master the essential skills to land a job as a machine learning scientist. You will augment your Python programming skill set with the toolbox to perform supervised, unsupervised, and deep learning. Trainees will also learn how to process data for features, train models, assess performance, and tune parameters for better performance. In the process, you’ll get an introduction to natural language processing (NLP), image processing, and popular libraries such as Spark and Keras.

Career Track highlights:

  • Includes 23 courses
  • Duration: 93 hours
  • Skills: Python, Machine Learning

Statistician with R career trackThe Statistician with R career track from DataCamp will help you to master the essential skills you need to land a job as statistician. Using statistics, you can help solve real-world problems in business, engineering, the sciences, and many other fields. You will learn and get hands-on experience on how to use statistical methods to explore and model data, draw conclusions from a wide variety of datasets, and interpret and report findings.

Career Track highlights:

  • Includes 14 courses
  • Duration: 56 hours
  • Skills: R, Statistics