Best Certification for Data Science
If you’re looking for a high-paying job in the data science field, you need to know where to start. But we’ve got some good news and bad news.
The good news is that data science is one of the most in-demand skills out there right now, with an average salary of over $100,000. The bad news is that it’s not easy to break into the field without proper training.
Luckily, there are plenty of data science courses that can help you get started. But what if you’re not sure where to start?
If you’re looking for a comprehensive course to build your data scientist skillset, look no further – we’ve got all the info you need right here. Let’s get started learning today with these data science certification courses.
1. Data Scientist Nanodegree Program (Udacity)
If you’re looking to become a data scientist, then look no further than Udacity’s Data Scientist Nanodegree Program. With this certificate, you’ll learn how to use Python for data science projects – so you can build functioning machine learning models and pipelines.
You will also be able to put all of what you’ve learned into action by working on your own open-ended Data Science project. Through this immersive program, you’ll build your portfolio and advance your career in a data science role with the skills you learn in this program.
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PROS
CONS
COURSES
- Solving Data Science Problems: Be able to present your findings, build effective data visualizations, and gain a deep understanding of the data science process.
- Software Engineering for Data Scientists: Get the skills you need that are essential for data scientists by learning how to build classes and create unit tests.
- Data Engineering for Data Scientists: You’ll get hands-on experience with the latest data science technologies and skills required to drive data science projects in the cloud.
- Experiment Design and Recommendations: Experience the power of advanced analytics and for testing A/B testing and recommendation systems.
- Data Science Projects: Take what you’ve learned throughout the program and build your own project in a real-world setting.
VERDICT
This program is designed by industry experts and will give you the skills and experience you need to succeed in this field. In this program, you will learn how to visualize data and build data engineering skills essential for data scientists. Additionally, you’ll work on real-world projects, run data pipelines, design experiments, build recommendation systems, and much more. So if you’re ready to jump into the world of data science, the Udacity Data Scientist Nanodegree program is the perfect place to start.
| Instructor | Udacity |
| Duration | 4 months (10 hours per week) |
| Certification | Data Scientist Nanodegree |
| Prerequisites | Python, SQL & Statistics |
| Skills Acquired | IBM Watson Studio, Python, SQL, Data Pipelines, and Statistics |
2. IBM Data Science Professional Certificate (IBM)
The IBM Data Science Professional Certificate will help you understand the basics of data science and give you the skills you need to work with data. You’ll learn how to use the tools, languages, and libraries used by professional data scientists, so you can start your career in this exciting field.
PROS
CONS
COURSES
- Data Science Tools and Methods: Prepares you to solve real-world business problems that can be tackled with data science.
- SQL and Analysis for Python: SQL is the language of databases, and this course will show you how to use it as part of your data science work.
- Visualization in Python: In this course, you’ll learn how to use your existing data to create meaningful visualizations and graphical representations.
- Machine Learning with Python: Gain skills for uncovering hidden insights and predicting future trends using machine learning with Python.
- Capstone Project: You will be able to showcase your Data Science skills and give yourself a competitive edge in the job market with a Capstone project.
VERDICT
With hands-on experience using real data sets, you’ll be ready to take on any challenge that comes your way. For instance, you will clean and analyze your data through the IBM Data Science Professional Certificate program. Plus, you’ll be able to publish your findings in a professional report. Become a data scientist with Python and begin your journey to becoming a confident data scientist.
| Instructor | IBM |
| Duration | 1 year (3 – 6 hours per week) |
| Certification | IBM Data Science Professional Certificate |
| Coursework | 10 skill-building courses |
| Skills Acquired | Python, SQL, Jupyter notebooks, IBM Watson Studio, R Studio, Pandas, SciPy, Scikit-Learn, Matplotlib, Seaborn, and Folium |
3. Professional Certificate in Data Science (Harvard)
Data Science is the science of extracting information from data. It includes understanding, predicting, and improving business decisions through data-driven insights. The field of data science has gained momentum in leveraging data for decision-making. The Professional Certificate in Data Science ensures that you get your hands on the skillset you need to excel in your career.
PROS
CONS
COURSES
- R Programming Basics: Learn how to effectively manage, analyze and visualize data from scratch with the R framework.
- Data Wrangling and Productivity Tools: Learn the methods of data wrangling, investigation and analysis so that you can work more efficiently with them. Gain knowledge on production techniques that will help you work effectively.
- Machine Learning: Study practical methods for applying machine learning techniques to real-world problems and creating scalable solutions.
- Capstone Project: Students get both hands-on experience and theoretical insight into data science problems with their own research project, while also finishing out their certification requirements.
VERDICT
In a world where data has become the most important asset, it’s no surprise that there are many professionals in data science. By utilizing data to make decisions and solve problems, they can help businesses thrive. Harvard University is now offering a Professional Certificate in Data Science, which can help you stand out from the crowd.
| Instructor | Harvard University |
| Duration | 1 year and 5 months (2-3 hours per week) |
| Certification | Professional Certificate in Data Science |
| Prerequisites | None |
| Instruction | 9 skill-building courses |
| Skills Acquired | R Programming, Statistics, Ggplot2, Dplyr, GitHub, and RStudio |
4. Data Scientist with Python (DataCamp)
Python is a must-know language for data scientists. And that’s what this track is all about. You’ll learn the ins and outs of Python, as well as how to use it for data science tasks like training decision trees and doing natural language processing (NLP). With DataCamp’s Data Scientist with Python track, you can gain the essential coding skills you need to succeed in this growing field.
PROS
CONS
COURSES
- Introductory and Core Python: From introductory to intermediate Python, learn the essential skills like NumPy, Pandas, and Matplotlib.
- Data Visualization: Enhance your data analysis with a practical introduction to data visualization and Matplotlib, the most popular open-source graphing library.
- Python Data Science Toolbox: Follow along in interactive tutorials and learn how to customize your own functions and handle errors.
- Applied Projects: From investigating Netflix movies, Github, to Android App Market, you will get hands-on experience extracting information and learning to code in Python.
VERDICT
This comprehensive Data Scientist with Python track will take you from beginner to expert, using real-world datasets to learn the statistical and machine learning techniques you need. Its interactive exercises will teach you how to manipulate and visualize data using some of the most popular Python libraries including pandas, NumPy, Matplotlib, and many more. But the best part is that you don’t need any prior coding experience because its experts will guide you every step of the way. Start your data science journey today with DataCamp.
| Instructor | DataCamp |
| Duration | 88 hours |
| Certification | Data Scientist with Python |
| Prerequisites | None |
| Coursework | 23 courses and 6 projects |
| Skills Acquired | Python, Pandas, NumPy, Matplotlib, Scikit-learn, SQL, Seaborn, Git, Natural Language Processing (NLP). |
5. MicroMasters® Program in Data Science (UC San Diego)
The MicroMasters Program in Data Science from UC San Diego offers 4 graduate-level courses that are designed with industry leaders in mind. These courses are taught by working professionals within this field who have years of relevant experience. Course topics include big data analytics, machine learning, artificial intelligence, statistics, data visualization, algorithms, and more.
PROS
CONS
COURSES
- Python for Data Science: Learn the foundations of Python to manipulate, analyze, and visualize complex datasets with Pandas, Git and Matplotlib.
- Probability and Statistics in Data Science using Python: Get a firm understanding of the power of probabilistic modeling and Python’s ability to gain insights for data science.
- Machine Learning Fundamentals: Get a comprehensive overview of machine learning, from the basic principles to practical applications.
- Big Data Analytics Using Spark: Unlock the power of big data with this hands-on course. This course covers everything you need to get started with big data analytics using the Jupyter notebook, MapReduce, and Spark as a platform.
VERDICT
The MicroMasters Program in Data Science from UC San Diego is a good alternative for those who would like to pursue an analytics degree or certificate without the extensive cost commitment or requirement of pursuing all the traditional coursework. With this program, students can complete their coursework online and receive a data science certificate upon completion.
| Instructor | UC San Diego |
| Duration | 4 months (10 hours per week) |
| Certification | MicroMasters® Program in Data Science |
| Skills Acquired | Python, Pandas, Git, Matplotlib, Jupyter Notebooks, MapReduce and Spark |
6. Data Scientist in Python (Dataquest)
The skills and tools necessary for a data scientist are changing, so this is why Dataquest is offering a Data Scientist in Python career path. The course starts with an overview of data science and how it can be applied in production. You will then explore the basics of programming in Python looking at functions, loops, and objects. Next, you’ll be introduced to tools such as Pandas, NumPy, Spark, and Matplotlib for data exploration. Finally, you will get hands-on learning where you will apply some of these techniques by exploring real-world datasets using machine learning.
PROS
CONS
COURSES
- Python and SQL: These courses will teach you the fundamentals of how to write Python code, how to use SQL, and combining the two. You’ll learn everything from loops, conditionals, dictionaries to Pandas and NumPy.
- Statistics and Machine Learning: For those interested in learning about statistics, probabilities and machine learning, these courses are designed to help you quickly grasp the concepts and practice through Dataquest.
- Deep Learning: Brush up on the fundamentals of deep learning and Apache Spark with this course, which starts with decision trees and a basic understanding of neural networks.
VERDICT
The Data Scientist in Python track from Dataquest is an online program that covers the essentials of the data science field. The track is designed to take you from beginner to intermediate level and provide you with a certificate upon completion to showcase on your CV/resume. This program is specifically tailored for people who are interested in learning more about data science but don’t know where to start.
| Instructor | Dataquest |
| Duration | 34 Modules |
| Certification | Data Scientist in Python |
| Prerequisites | Beginner Python |
| Skills Acquired | Python, SQL, Apache Spark, NumPy, Pandas, Matplotlib, Kaggle, Jupyter Notebooks, Git, and Map Reduce |
7. Applied Data Science with Python Specialization (University of Michigan)
Text mining, inferential statistics, machine learning: the future is now for data science. Data has become a driving force in our economy and society because of its immense potential to allow us to uncover insights that would otherwise be impossible. The five-course Applied Data Science with Python Specialization from the University of Michigan will teach you how to use Python as a gateway into the world of data science.
PROS
CONS
COURSES
- Introduction to Data Science in Python: Learn the basics of data manipulation and cleaning techniques with the popular Python pandas library and how to effectively utilize functions such as groupby, merge, and pivot tables.
- Charting, Plotting, and Data Visualization: Get a complete introduction to how to visualize information. Learn how to plot, chart, and visualize information with Matplotlib.
- Applied Machine Learning in Python: Understand the difference between supervised and unsupervised learning methods and identify machine learning techniques.
- Projects in Python: Perform a series of projects using Python including text mining and social network analysis.
VERDICT
The Applied Data Science with Python Specialization from the University of Michigan discusses how to apply their skills towards applied data science with Python. This specialization will help students learn how machine learning works with Python and statistics in order to build predictive models that are suitable for solving real-world problems.
| Instructor | University of Michigan |
| Duration | 5 months (7 hours per week) |
| Certification | Applied Data Science with Python Specialization |
| Level | Intermediate |
| Skills Acquired | Python, Pandas, Matplotlib, Scikit-learn, Natural Language Toolkit (NLTK), and NetworkX |
8. Data Science for Business Leaders Nanodegree (Udacity)
There are no shortcuts to mastering data science, but there are some tricks that can help you speed up the learning process. Whether you are a business leader or not, it is important to understand how data science can impact your company. The Data Science for Business Leaders Nanodegree offers numerous benefits for business leaders. If you want to learn about the importance of data science for business leaders and how it can impact any company, this nanodegree is the right step forward.
PROS
CONS
COURSES
- Introduction to Data Science: You’ll learn how Data Scientists create insights and open doors for your business.
- Business Case for Data Science: This course will teach you how to develop a data science strategy that aligns with a business’s broader strategic objectives and identify opportunities for data science-based transformation.
- Human Capital of Data Science: Data science is the future of the information age and is becoming an ever-increasingly important strategic business function. Learn why data science adds value to the organization by improving decision-making and leveraging data to help people make better, more data-driven decisions.
- Data and Machine Learning Infrastructure Strategy: Data science and machine learning are redefining the role of business intelligence and analytics. Build a data infrastructure that best supports the overall data science initiative and machine learning strategy.
- Capstone Project: Learn to build a data plan from your first day that drives transformation in your business until day 100. This capstone project will help you see the impact of your strategies and the potential of your data.
VERDICT
Data science isn’t just a buzzword; it’s a powerful tool for solving business challenges. If you are looking for ways to use data science to improve your current processes as well as grow your business, the Data Science for Business Leaders Nanodegree will open your eyes to how data science can make a difference. You will learn strategies to implement data science in your strategic plan under the wing of instruction from Udacity, a global leader in education and instruction.
| Instructor | Udacity |
| Duration | 4 – 8 weeks (5 hours per week) |
| Certification | Data Science for Business Leaders Nanodegree |
| Prerequisites | Statistics, Probability, and Business Experience |
| Skills Acquired | Data Science Implementation, Strategic Planning, Capstone Project |
9. Data Science Specialization (Johns Hopkins)
The Data Science Specialization by Johns Hopkins takes you from zero into the world of data science. You’ll learn the basics like how to read and write R Programming code, and effective coding practices such as when and where to use loops, conditionals, functions, and modules. Finally, you’ll cap it off with a data science capstone project drawn from a real-world situation.
PROS
CONS
COURSES
- R Programming: Learn the key aspects of programming in R and how to implement statistical programming skills in R while getting to grips with the most important parts of the package, including reading, data manipulation, and exploration.
- Statistics with R: Get an introduction to R programming for data analysis and understanding before diving into more advanced statistical methods. For instance, conduct exploratory analyses, build regression models, and learn statistical inference.
- Machine Learning: This course will teach you the basics of applying machine learning to build powerful predictive models. By the end of this course, you will have a better understanding of the practical challenges of building predictive models and the know-how to tackle them.
- Capstone Project: Get practice applying your data science skills to real-world problems. Use the skills and knowledge you’ve gained throughout your courses to create an impactful final data product.
VERDICT
If you are looking for a specialization that gives you a leg up in the field of statistics, data mining, and predictive modeling, the Data Science Specialization by Johns Hopkins University may be the perfect fit for you. Although it’s heavy in R Programming, it will teach you how to extract information from data and make predictions using statistical methods.
| Instructor | Johns Hopkins University |
| Duration | 11 months (7 hours per week) |
| Certification | Data Science Specialization |
| Level | Beginner |
| Skills Acquired | R Programming, RStudio, Regression, Machine Learning, RegEx, and ANOVA |
10. Data Scientist Career Path (Codecademy)
If you want to break into the field of data science, becoming certified in Codecademy’s Data Scientist Career Path is a good place to start. The Data Scientist Career Path from Codecademy is an online course where you learn the fundamentals of statistics, big data, and machine learning with interactive Python code examples. Throughout the coursework, it challenges you with interactive projects to put your skills to the test.
PROS
CONS
COURSES
- Python Fundamentals and Project: Get started learning the fundamentals of Python, and use your understanding of Python syntax to sort and analyze data. You will learn about different data types and finish with a Python project analyzing medical insurance costs.
- Data Wrangling and Manipulation with Pandas: You will learn the basics of pandas, including how to import, clean, reshape, and aggregate data. Once you have learned this, you are ready to start using pandas for data wrangling and manipulation.
- Data Visualization and Portfolio Project: This course features advanced data visualization and portfolio project skills necessary for professionals in the field. You will learn data visualization techniques to better understand, analyze, and visualize your data. You will also understand the power of using your understanding of data visualization to create dynamic visualizations with a project regarding GDP and life expectancy.
- Machine Learning and Deep Learning Project: Gain a firm foundation in machine learning and deep learning. By the end of this course, you will have a firm grasp of supervised learning, unsupervised learning, and clustering techniques.
VERDICT
There’s no better time to be a data scientist than now. The Data Scientist Career Path spans a wide range of course material such as data manipulation, visualization, and machine learning in Python. It will challenge you continuously through projects to reinforce what you’ve learned. The skills and tools you need to excel in this field are available if you’re willing to put in the effort. Take the first step through the online Codecademy platform.
| Instructor | Codecademy |
| Duration | 35 Weeks |
| Certification | Data Scientist Career Path |
| Course Material | 21 Lessons |
| Skills Acquired | SQL, Python 3, NumPy, Pandas, Matplotlib, and Scikit-learn |
Best Data Science Certification Courses
Data scientists are one of the highest-paid tech professionals out there that’s quickly growing in popularity. It’s not only its high salaries and growth that are unique to data science, but it also has opportunities in many different industries.
LinkedIn data has shown a +650% growth rate since 2012, and the average annual salary for jobs with “data scientist” in their title hit $120,000+ last year.
If you want to get on board with this lucrative career opportunity, here is a list of the best data science courses and certification options to help you get started with your journey.
Consider enrolling in one of the data science training courses today and you’ll be able to land a job as a data scientist or just better understand how it all works. Otherwise, here are some other certification courses to check out:
- 10 Data Visualization Certification and Courses
- Data Analyst Certification For Beginners
- R Certification Courses for Statistical Computing
- 10 Python Courses and Certificate Programs
- SQL Certification Courses – Structured Query Language
- Artificial Intelligence Courses – Learn AI
