Over the course of several years and 100+ hours watching course videos, engaging with quizzes and assignments, reading reviews on various aggregators and forums, I’ve narrowed down the simplest data science courses and certifications available to the list below.
Best Data Science Courses & Certifications for 2020:
Criteria for grasping Data science courses and certifications
The selections here are geared more towards individuals getting started in data science, so we’ve filtered the data science courses and certifications supporting the subsequent criteria:
A. The course certainly goes over the whole data science process
B. The course utilizes well known open-source programming devices and libraries
C. The instructors cover the essential, hottest machine learning algorithms
D. The course features a good combination of theory and application
E. The course must either be on-demand or available monthly approximately
F. There are hands-on assignments and projects
G. The instructors are subsequently engaging and personable
H. The course has excellent ratings – generally, greater than or adequate to 4.5/5
This course series is one among the foremost enrolled in and highly rated course collections during this list. JHU then did a fantastic job with the balance of breadth and depth within the curriculum. One thing that’s included during this series that’s usually missing from many of knowledge science courses may be a complete section on statistics, which is that the backbone to data science.
Overall, the info Science specialization is a perfect mixture of theory and application using the R programing language. As far as prerequisites go, firstly, you ought to have some programming experience and secondly, you’ve got an honest understanding of Algebra. Previous knowledge of algebra and/or Calculus isn’t necessary, but it’s helpful.
Price – Free or $49/month for certificate and graded materials
Provider – Johns Hopkins University
- The Data Scientist’s Toolbox
- R Programming
- Getting and Cleaning Data
- Exploratory Data Analysis
- Reproducible Research
- Statistical Inference
- Regression Models
- Practical Machine Learning
- Developing Data Products
- Data Science Capstone
An extremely highly rated course — 4.9/5 on SwitchUp and 4.8/5 on CourseReport — which is taught live by a knowledge scientist from a top company. this is often a six-week-long data science course that covers everything within the entire data science process, and it’s the sole live online course during this list. Furthermore, not only will you get a certificate upon completion, but since this course also accredited, you’ll also receive continuing education units.
Two nights per week, you’ll join the trainer with other students to find out data science as if it had been a web college course. Not only are you ready to ask questions, but the trainer also spends overtime for office hours to further help those students which may be struggling.
Price — $750
- Computer Science, Statistics, algebra Short Course
- Exploratory Data Analysis and Visualization
- Data Modeling: Supervised/Unsupervised Learning and Model Evaluation
- Data Modeling: Feature Selection, Engineering, and Data Pipelines
- Information Modeling: Advanced Supervised/Unsupervised Learning
- Information Modeling: Advanced Model Evaluation and Data Pipelines | Presentations
The University of Michigan, who also launched a web data science Master’s degree, produce this fantastic specialization focused the applied side of knowledge science. this suggests you’ll get a robust introduction to commonly used data science Python libraries, like pandas, nltk, sci-kit-learn, and networkx, and find out how to use them on real data.
This series doesn’t include the statistics needed for data science or the derivations of varied machine learning algorithms but does provide a comprehensive breakdown of the way to use and evaluate those algorithms in Python. due to this, I feel this can be more appropriate for somebody that already knows R and/or is learning the statistical concepts elsewhere.
Price – Free or $49/month for certificate and graded materials
Provider – University of Michigan
- Introduction to Data Science in Python
- Applied Plotting, Charting & Data Representation in Python
- Applied Machine Learning in Python
- Applied Text Mining in Python
- Applied Social Network Analysis in Python
MicroMasters from edX are advanced, graduate-level courses that count towards a true Masters at select institutions. Within the case of this MicroMaster’s, completing the courses and receiving a certificate will count as 30% of the complete Master of Science in Data Science degree from Rochester Institute of Technology (RIT).
Since these courses are geared towards prospective Master’s students, the prerequisites are above many of the opposite courses during this list. Since the primary course during this series doesn’t spend any time teaching basic Python concepts, you ought to already be comfortable with programming. Spending a while browsing a platform like Treehouse would probably get you up to hurry for the primary course.
Overall, I found this MicroMaster’s to be an ideal mixture of theory and application. The lectures are comprehensive in scope and balanced superbly with real-world applications.
Price – Free or $1,260 for certificate and graded materials
Provider – UC San Diego
- Python for Data Science
- Probability and Statistics in Data Science using Python
- Machine Learning Fundamentals
- Big Data Analytics using Spark
Dataquest is a fantastic resource on its own. Albeit you’re taking other courses on this list, this is an outstanding complement to your online learning.
Dataquest foregoes video lessons and instead teaches through an interactive textbook of sorts. Every topic within the data science track is amid several in-browser, interactive coding steps that guide you through applying the precise topic you’re learning.
Price – 1/3 of content is Free, 29/month for basic, 49/month for Premium
Here’s a condensed version of the curriculum:
- Python – Basic to Advanced
- Python data science libraries – Pandas, NumPy, Matplotlib, and more
- Visualization and Storytelling
- Effective data cleaning and exploratory data analysis
- Command-line and Git for data science
- SQL – Basic to Advanced
- APIs and Web Scraping
- Probability and Statistics – Basic to Intermediate
- Math for Machine Learning – algebra and Calculus
- Machine Learning with Python – Regression, K-Means, Decision Trees, Deep Learning and more
- Natural Language Processing
- Spark and Map-Reduce
Besides, the essential mathematics you ought to be comfortable with:
- Statistics (Frequentist and Bayesian)
- Linear Algebra
- Basic calculus