Get a comprehensive guide on how to learn Python for data science. This article outlines the various careers that commonly use Python for data science, provides free resources for learning, and includes an insight into the versatility of Python in machine learning and artificial intelligence.
If you’ve always wanted to learn Python for data science but can’t figure out how to get started, this guide is for you. Here, you’ll learn more about the various ways to learn Python for data science, free resources to take advantage of, and the types of careers that commonly use Python for data science.
Python is among the most popular programming languages in the world, and many tech professionals learn it before moving on to other languages. According to leading publications, data science and machine learning pros consider Python their go-to programming language. Python is an essential skill for many development and data science roles, including:
Artificial intelligence (AI) and machine learning (ML) are areas where Python for data science rules the roost. Building ML models and applying ML algorithms typically includes libraries like Scikit Learn or PyBrain. Data analysis requires Python libraries like Pandas and NumPy. And visualization with Matplotlib or Seaborn is popular in Python for data science.
Read more about what Python is and why you should learn it for data science.
Python is advantageous for data science professionals of all kinds. Its ease of use and scalability make it the top choice for Data Scientists, Data Engineers, and Data Analysts in virtually every sector of the economy.
Because Python is both easy to learn and powerful, its libraries and frameworks can be ideal for dealing with mathematical functions, data structures, and visualization. Here are some of the most common uses for Python in data science.
Python for data science is ubiquitous today, with virtually every industry using it where possible. According to the Bureau of Labor Statistics, industries with the highest level of Data Scientist employment include:
These categories illustrate several things.
First, companies need Python data science expertise at the highest levels, including management positions like Senior Engineer, Tech Lead, and Product Manager. Second, C-suite executives need data science expertise at their fingertips from trusted managers. And third, science is only one area where data science skills are needed, while business and finance, along with high tech, lead the pack.
A complete list of what industries use Python for data science and for what tasks is beyond the scope of this article. Some of the most well-known examples include:
As Forbes noted in its Top Five Data Science Trends That Made An Impact In 2022, Python has emerged as “the go-to programming language for data science.” The article references multiple dominant data science libraries, including:
If you’re planning to study Python for data science, you can go into it knowing you’ll learn crucial skills and information. Top roles typically requiring Python for data science today include:
Python for data science isn’t only for IT or software development, either. Sectors as diverse as banking/finance, manufacturing, agriculture, and media require Python data science expertise, and public sector roles like government and academia can require it, too.
Read more about why you should learn Python for data science.
Python for data science novices often find it challenging when they try to determine the best way to master the popular programming language. Whereas busy professionals may already have some data science skills, students beginning their careers may want to get in-depth training in a concentrated time frame.
Fortunately, Python data science students can find many educational options, both in-person and live online. Bootcamps, certificate programs, and self-paced classes provide information and, in many cases, hands-on experience. Consider the following:
Read the full guide on how to learn Python for data science.
Those not yet ready to dive into a full-scale bootcamp or certificate program can still get an overview of Python for data science. Start learning Python for data science online for free. In this introductory course, you’ll learn fundamentals like:
Additional free classes include Data Processing Using Python from Nanjing University, Data Science Math skills from Duke University, and the University of London’s Foundations of Data Science: K-Means Clustering in Python.
Read about more free Python and data science videos and online tutorials.
You may think Python for data science will be challenging to learn, particularly if you have no coding experience. However, many students are surprised to learn that Python is the most popular programming language among data science professionals and one of the easiest to master. Python’s open-source license means an entire universe of libraries can be used free of charge, and its worldwide support community is always a mouse click away.
Before you start learning Python for data science, you should have a plan for how and where you’ll apply the knowledge you gain. Python programming fundamentals for a Data Analyst may differ from those of a Software Engineer. You should have basic computer skills, but you can use Python on Mac OS, Linux, or Windows.
You can download Python’s libraries and frameworks for free and find many online Python seminars and tutorials at no cost. However, you’ll eventually want to enroll in formal, paid training. If you learn Python as part of a broader data science curriculum, your approach will be different than if you want to focus on Python in a narrower sense.
Read more about how difficult it is to learn Python for data science.
Python is a primary component of data science, but not every data science professional uses it equally. Many programming beginners start with Java or R, but most learn Python before other languages.
In recent years, R has emerged as the other “big” data science language besides Python. While Python may be easier to learn, R has several advantages in the eyes of many data pros. Consider the following:
Python is typically the language of choice for handling large quantities of data. Python is also commonly tied to deep learning algorithms, web scraping, and running workflows. On the other hand, many data science pros prefer R for data visualization and statistical calculation.
Data Scientists and other computer science pros may prefer Python for many tasks. However, Data Analysts, Financial Analysts, and Business Analysts may use R more. Both have advantages and drawbacks, so you may want to learn both, depending on your role and the sector or industry you choose.
For more on tools and skills in different positions, check out Noble Desktop’s Learning Resources.
When choosing the best way to learn data science, you should know how and where you want to apply this high-level programming language. Beginners may not be ready to invest in formal training, and there’s nothing wrong with reading articles or watching video tutorials. A free online seminar like Noble Desktop’s Intro to Python Fundamentals can be a great place to begin.
If you want to develop a working knowledge of Python for data science, plug a skill gap, or grow within your current role, consider enrolling in a bootcamp. Noble’s Python for Data Science Bootcamp or Python Data Science & Machine Learning Bootcamp can get you started.
Want to master Python for data science for a new career or to pivot to a new industry? Check out programs like the Data Science Certificate or Data Analytics Certificate. These immersive programs cover everything from Python for data science fundamentals to relational databases.
Other factors in your decision-making process can include your budget, availability, prior knowledge of the topic, and whether you prefer to learn live online or in person.
Because Python for data science involves two potentially different disciplines—Python programming and the broader data science field—not every student approaches it the same way. How and where you plan to use the knowledge you gain from Python for data science training may dictate your approach.
Noble Desktop offers multiple avenues to learn data science. Their Data Science Certificate includes Python programming fundamentals, machine learning, SQL to query databases, and plotting and dashboard libraries. This program prepares attendees for entry-level positions in data science and Python engineering.
Another option is Noble’s Python for Data Science Bootcamp. A hands-on 30-hour course, the bootcamp includes training in Numpy, Pandas, Matplotlib, and linear regression. Students can save by taking the Python for Data Science Bootcamp as part of the Data Science Certificate program as well.
If you prefer to peruse all the Python for data science training Noble Desktop offers, check out the Python Classes page. Here you’ll find bootcamps and certificate programs as well as shorter courses. Top certificate programs include:
Popular bootcamp options include:
Other training options include:
Noble Desktop’s bootcamps and certificate programs earn high marks from graduates. They are available live online or in-person in New York City. Additional perks include a verified Certificate of Completion and free retakes within a year after graduation. Many certificates and bootcamps also include 1-on-1 mentoring: check course descriptions for more information, including any prerequisites.
Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to clean and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.
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