Best Python Courses for Non-programmers: Learn to Use Python in Your Workflow
Find course recommendations for specific non-programming fields and their day-to-day tasks that Python can help with.
Best Python Courses for Non-programmers: Learn to Use Python in Your Workflow
The best way to learn Python as a non-programmer is to learn how to use Python to ease and simplify your day-to-day tasks. This begins by understanding the basics and then learning how to do specific tasks.
Here, we will go into specific non-programming fields and recommend courses based on how Python can help with your day-to-day tasks.
Programiz Recommends
As mentioned above, you should learn the basics of Python before you learn any specific applications. It will help you avoid many pitfalls that beginners fall into when starting with something unfamiliar.
If you want a good course to understand Python basics, start our Learn Python Basics course.
For Business Analysts
As a business analyst, your day-to-day mostly consists of:
- gathering and analyzing data
- conducting market research
- generating business reports
- understanding business needs and objectives
So, basically, staring at numbers all day.
In these, you are spending a lot of time and energy sifting through numbers manually. Here is where Python comes in handy.
| Task | How Python Can Help |
|---|---|
| Gathering and analyzing data | Provides libraries like Pandas and NumPy for efficient data manipulation and analysis, enabling quick extraction of insights from large datasets. |
| Conducting market research | Automates data gathering from online sources and facilitates analysis for identifying trends and patterns with libraries like BeautifulSoup. |
| Generating business reports | Automates report generation by processing and visualizing data, and allows for interactive report creation with Jupyter Notebooks. |
After you are comfortable with Python basics, you should go with the IBM Data Analyst Professional Certificate on Coursera.
It will teach you how to work with data quickly with Python libraries like Pandas and NumPy.
For Digital Marketers
Digital marketers deal with repetitive tasks like performance numbers analysis and campaign setups often — sometimes too often to focus on important creative tasks like marketing messages and product positioning.
Python can help reduce this monotony and free up time for more important stuff.
| Task | How Python Can Help |
|---|---|
| Marketing automation | Facilitates automation of marketing workflows through Pandas, allowing marketers to streamline repetitive tasks such as email campaigns, lead generation, and content distribution. |
| Campaign performance analysis | Automates the analysis of campaign data through Matplotlib and NumPy, providing insights into performance metrics such as click-through rates, conversion rates, and ROI. |
| Data analysis and visualization | Offers tools for processing and visualizing data, enabling marketers to analyze trends and patterns and communicate insights effectively. |
| SEO analysis | Automates the analysis of website data for SEO purposes, helping identify areas for improvement and optimizing search engine rankings through BeautifulSoup. |
| Gathering information from the web | Automates web scraping tasks to collect data from various online sources, including competitor websites, industry news sites, and social media platforms. |
| Social media sentiment analysis | Analyze social media data with NLTK and TextBlob to gauge audience sentiment, identify trends, and monitor brand perception, enabling you to adapt strategies accordingly. |
As a beginner, we think you should start with small automation-related things, like emails.
For that, Automate The Boring Stuff with Python Programming course on Udemy should be a great resource, particularly the 'Email' section of the course.
Or you can read Automate The Boring Stuff with Python for free. The course is inspired by the book, and you can directly jump to the email-related chapter.
Of course, know the basics first. If you do not know it yet, start learning here.
For Financial Planners
As a financial planner, your job consists mainly of three things: financial calculations, investment portfolio analysis, and risk assessment. The things you value the most are time and accuracy of your calculations and predictions.
Learning Python helps you with all of them and more.
| Task | How Python Can Help |
|---|---|
| Financial calculations | Automates complex financial calculations, including cash flow analysis, present value calculations, and loan amortization schedules, saving time and reducing errors. |
| Investment portfolio analysis | Provides tools like Pandas for analyzing investment portfolios, including performance metrics, asset allocation, and risk-adjusted returns, enabling planners to make informed investment decisions. |
| Risk assessment | Facilitates risk assessment by analyzing historical data, simulating potential scenarios, and calculating risk metrics such as value at risk (VaR) and conditional value at risk (CVaR). |
Learn all these skills through the Python and Statistics for Financial Analysis course from Coursera to improve your worth as a financial planner and analyst.
It will teach you Python and its useful libraries by using examples that financial analysts and planners will be familiar with.
For Accountants and HR Professionals
Accountants and HR professionals deal with plenty of important things daily, like
going through and analyzing financial statements, budgeting, asset maintenance, policy and compliance management, etc.
Many of these end up being manual tasks that consume hours, if not days. Here is how Python can help you with them:
| Task | How Python Can Help |
|---|---|
| Data analysis | Provides tools for analyzing large datasets, identifying patterns, and extracting insights to inform decision-making. |
| Report generation | Automates report generation by processing and visualizing data, and allows for customized report templates and formatting. |
| Process optimization | Facilitates process automation and streamlining, allowing the elimination of manual tasks, reducing errors, and improving efficiency. |
| Compliance management | Automates compliance checks, generates reports, and monitors adherence to ensure compliance with regulations and policies. |
You should, however, start with something really simple, like automating your Excel sheets. For that, we recommend the Python for Accountants course on Udemy.
As an additional resource, use this Pythonic Accountant YouTube playlist. It has videos about dealing with trial balances and extracting account data.
For Educators and Trainers
Python can be very helpful to someone working in the education sector, especially because it can automate many of the more repetitive tasks. These could be anything from grading students and creating mark sheets to sending bulk emails and coming up with curriculum and test schedules.
| Task | How Python Can Help |
|---|---|
| Student assessment and grading | Python can automate grading processes, analyze student performance data, and generate personalized feedback reports, saving time and providing valuable insights. |
| Lesson planning and curriculum development | Python can assist educators in organizing and managing lesson plans, creating interactive learning materials, and developing curriculum resources. |
| Classroom management | Python can help educators manage classroom resources, schedule activities, and communicate with students through automation tools and interactive platforms. |
| Professional development and research | Python can support educators in conducting research, analyzing educational data, and exploring new teaching methodologies through data analysis and visualization. |
Grading students and analyzing their records is one of the more tedious tasks that you might have to do. So, you should learn how to do that using Python first.
Our Python NumPy course teaches you all you need to learn about it, plus a final project that teaches you exactly that: analyzing student records.
Final Thoughts
As a non-programmer, you should learn Python for a task that lets you apply your Python knowledge daily. This will not only keep the learning process interesting but also make your effort worthwhile.
However, jumping in blind is bad. If you are learning Python to simplify your tasks, start with the very basics, become proficient, and only then learn particular, specialized applications.
If you are just starting out with Python, we recommend you build a solid programming foundation first with our Learn Python Basics course before you learn the advanced stuff.