Best Free Python for Data Science Resources & Tutorials

Many professionals are eager to learn Python for data science but hesitate because of the perceived up-front costs. Luckily, most programming languages are open-source and free to use, and Python is no exception: you can download Python and its libraries and frameworks one hundred percent free. 

The cost of Python for data science education usually comes when new programmers begin paid training. Before that, however, a surprising number of free resources can help beginners get started in this exciting field. 

You can find out more about the different types of free resources and tutorials available to help you learn Python for data science below.

What is 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:

• Data Scientist
• Data Engineer
• Software Engineer
• Data Analyst
• Python Developer

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. 

What Can You Do with Python 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.

• Data Analysis - Python is easy to read and write, so it’s commonly used for complex data analysis—particularly handling large datasets. Top Python libraries for data analysis include:

• NumPy
• Pandas
• SciPy

• Data Visualization - Data science often requires visualization tools. Data professionals use charts, graphs, and even maps to present data in easy-to-digest ways. Top Python libraries for data visualization include:

• Matplotlib
• Plotly
• Seaborn

• Artificial Intelligence and Machine Learning - Machine learning, or ML, is a subset of artificial intelligence (AI). Data science pros use ML libraries like Scikit Learn for data classification and linear regression. Top Python libraries for AI and ML include:

• Scikit Learn
• PyBrain
• TensorFlow

Free Introductory Classes & Materials

Careers in Python for data science vary, from entry-level Business Analyst positions to Senior Data Scientist careers. Wages and salaries also vary, not only by industry but also by geographic location. To get started in this exciting field, you’ll most likely seek to learn more through free online resources—blogs, prerecorded videos, and live webinars.

Course providers encompass a wide range of resources, too. Many colleges and universities offer Python or data science training, typically as part of four-year degree programs. Other course providers, like Noble Desktop, provide bootcamps and certificate programs that allow attendees to complete training in a more concise timeframe.

Most beginners in Python for data science, however, prefer to learn at least some fundamentals through free resources before committing to a full-length course of training. You can find out much more about Python for data science on Noble Desktop’s blog. Topics here include:

• Exchanging Excel for Python
• Making a Twitter Bot In Python
• Intro to SQL

The Noble Desktop Learn Hub is another rich resource for introductory materials. Check the Data Science section for resources like SQL, Tableau, and Power BI, and the Python section for over 40 Python-adjacent resources. Topics here include:

• Zip Function in Python
• Python Vs. Excel for Data Analytics
• Writing Data into a Text File Using Python
• Explaining Tuples in Python
• Filtering a String With Python

Other Free Information Sources

In addition to the many free blog posts, webinars and tutorials you can find online, you can also find a wealth of information by reading up on Python for data science industry news. Consider these resources:

• Tech Company Websites - General information and even specific news stories often run on big tech websites. Check out Alphabet’s Google blog, Python’s blog, or the Salesforce Blog for news and updates.

• Data Science Publications - Popular data visualiztion tool Tableau hosts an elearning resource on its website. There’s a Top 10 Best Data Science Blogs to Follow article featuring resources like Data Science Central and SmartData Collective. 

• Industry News - If you know which industry you plan to enter with your Python for data science skills in hand, check out some of the biggest online news resources. FinTech pros may want to follow FinTech Nexus News, machine learning pros can read the OpenAI blog, and data analytics pros may want to check out Analytics Insight.

Key Insights

• Most programming languages are open-source and free to use, and Python for data science is no exception: you can download Python and its libraries and frameworks for free.

• Data science pros consider Python their go-to programming language.

• Top roles in Python for data science include:

• Data Analyst
• Data Scientist
• Software Engineer
• Data Engineer
• Machine Learning Engineer

• The most common uses for Python for data science are data analysis, visualization, and artificial intelligence (AI), including machine learning (ML).

• Top Python libraries for data analysis include:

• NumPy
• Pandas
• SciPy

• Top Python libraries for data visualization include:

• Matplotlib
• Plotly
• Seaborn

• Top Python libraries for artificial intelligence (AI) and machine learning (ML) include:

• Scikit Learn
• PyBrain
• TensorFlow

• You can get an immersive Python for data science education through an in-person or live online course with Noble Desktop. Among their most popular options are:

• Python for Data Science Bootcamp
• Data Science Certificate
• FinTech Bootcamp

Learn Python for Data Science with Hands-on Training at Noble Desktop

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:

• Data Science Certificate
• Software Engineering Certificate
• Data Analytics Certificate

Popular bootcamp options include:

• Python for Data Science Bootcamp
• Python Programming Bootcamp
• FinTech Bootcamp
• Cybersecurity Bootcamp

Other training options include:

• Python for Automation
• Cybersecurity with Python
• Python for Network Security

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.