Can I Learn Python in 3 Months?

Although some experts say anyone can learn Python fundamentals in a few weeks or even days, the answer to this question is more nuanced. Consider the following examples.

First, imagine a person who approaches Python with no coding experience whatsoever. This Python beginner can take a seminar or tutorial and, in a short period, learn a few basics. However, obtaining information and retaining it are two different things.

Next, imagine someone who takes a bootcamp or a certificate program that features Python or includes Python in a broader data-centered or development curriculum. The program runs for four weeks full-time or 20 weeks part-time, including 1-on-1 mentoring, supplemental materials, and hands-on live training.

An example of this second scenario is the Data Science Certificate program from Noble Desktop. This course demonstrates that you can gain much knowledge in a few months or less, including libraries and frameworks, and get practical, hands-on experience. Among the many success stories from the certificate program are graduates who call it “the best value class out there,” assuring potential students that the program “prepared me well to use and apply Python.”

Of course, it can take years to become a true Python master, and lifetime learning is continuous, especially on the job. Read on to learn more about the Python skills a beginner can achieve in three months or less.

How Much Python Can I Learn in 3 Months? 

Different Python-centered careers require different tools and skills. When learning computer programming languages, many people opt for instructor-led classes where they can get assistance when needed and receive real-time feedback on their code. However, Python is unique in that development professionals typically learn some things that data science pros may not and vice versa. Consider the following tools and skills you can learn in three months or less.

Data Visualization & Dashboards - Data science often requires visualization tools like Tableau or Power BI. 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

Libraries - While Matplotlib, Plotly, and Seaborn are popular for Python data visualization, many other libraries and frameworks are essential for data and development professionals. Think NumPy for scientific computing, Scikit-learn or Tensorflow for machine learning, and Eli5 for debugging application development.

Frameworks - Frameworks are also essential for development and data pros, and some Python frameworks apply to both fields. Django REST is among the most popular with back-end development pros, where REST stands for representational state transfer. Top Python frameworks for data professionals include SciPy, Pattern, and Flask.

Of course, there are differences between what you can learn in a full-time class, part-time class, or through self-teaching. If you teach yourself Python skills and tools, moving from theoretical knowledge to practical application can take a long time. However, in an immersive program like the Data Science Certificate from Noble Desktop, you will learn:

• SQL for communicating with databases
• NumPy and Pandas for data analysis
• Matplotlib for graphs and visualizations
• Dash Enterprise for interactive dashboards
• Scikit-learn for logistic regression

One of the primary advantages of the immersive bootcamp/certificate learning model is that you can learn advanced techniques during the latter part of the program. Course providers like Noble Desktop build training modules on previous lessons. As a Python novice, you start with beginner-level information and hands-on exercises, creating a solid foundation. Intermediate and advanced training follows, so you qualify for an entry-level position when you graduate from a course like the Data Science Certificate.

The Python Developer Certificate provides comparable results for development beginners. You can learn much in three weeks full-time, as this program comprises 90 hours of instruction and includes four 1-on-1 mentoring sessions. The curriculum combines a Python Programming Bootcamp and Python Web Development with Django. Applicants can also receive a bonus 30-hour class at no additional charge and can choose among Python with Data Science, Python Machine Learning, or Python Data Visualization and Interactive Dashboards. Please note that applicants should have HTML/CSS knowledge comparable to that gained in the Noble Desktop Web Development with HTML & CSS class before enrolling.

How Can I Learn Python More Quickly?

If you want to learn Python quickly, you can master fundamentals in less than three months. How you approach it, however, can depend on factors like your previous experience, availability, and budget.

First, consider taking advantage of free resources. The Noble Desktop website features numerous free seminars and tutorials, which can go a long way toward orienting you to Python programming.

Secondly, understand what industry-specific skills you need to know. For example, are you looking to begin a finance career? If so, you can get your introductory Python training through a course like the FinTech Bootcamp. This immersive program offers the same Python for Data Science, Automation, Machine Learning, Data Visualization/Interactive Dashboards, and SQL Bootcamps as the Data Science Certificate. It also includes a bonus Python for Finance or Financial Modeling Bootcamp as a free elective. These programs give FinTech pros the necessary tools to work with APIs, Python financial libraries, and Excel formulas and functions.

Other tech pros will focus on Python as part of a broader machine learning (ML) education. For them, the Python Data Science & Machine Learning Bootcamp may be the way to start. The immersive 96-hour course is available full-time or part-time and includes four 1-on-1 mentoring sessions. Full-time participants can complete this beginner-friendly bootcamp in a month, learning Python for automation, ML, data science, and data visualization.

If you want to master Python for development, the approach can be quite different. Software or web app developers do not typically learn all the same tools as data science or analytics pros, though some of their skill sets overlap. A great way to start hands-on Python training for any career is the 30-hour Python Programming Bootcamp. This unit is available separately, but you can save time and money if you take it as part of the Python Developer Certificate program. You might sit alongside data science or analysis beginners in the Python Programming Bootcamp, as the Data Science Certificate and FinTech Bootcamp include this essential training unit.

Although the Python Developer Certificate starts with the Python Programming Bootcamp, its larger unit is a 60-hour Python Web Development with Django module. This section covers everything from using Django for web applications to querying models and API endpoints. Early registrants may also be eligible to receive a bonus Python elective at no additional charge. Check course listings for details, including any prerequisite information.

If you want to dive in and learn Python as part of a broader full-stack curriculum, consider the intensive Software Engineering Certificate program. The course comprises a 510-hour program of hands-on Python, HTML/CSS, JavaScript, and MERN tech stack training. Participants complete the certificate in 20 weeks full-time and receive 12 additional 1-on-1 mentoring sessions. Although it’s closer to six months than three, this certificate allows beginners to go from no experience to qualifying for entry-level software engineering or full-stack development positions.

You can learn Python well in three months. However, most tech professionals have to do much more than Python programming once on the job. If you already work in your field of choice and are taking one of these courses to level up to another position, consider what essential industry-specific knowledge you have or need to have. For example, FinTech pros may need to know portfolio management, Marketing Analysts may need data visualization tools like Tableau, and Web Developers may need multiple languages like JavaScript, PHP, and Ruby on Rails. However, an analytics pro in FinTech may have a much different knowledge of industry-specific information than a marketing professional in the event management field. Read on to learn more about the specific skills you may need after you master Python fundamentals.

What Python Skills Will I Need to Learn After 3 Months?

Once you have completed three or more months of Python experience, you may be ready for more advanced training. As in any endeavor, the skills and tools you will need depend on numerous factors, from the type of Python training you received to your industry or sector, how you will use Python, and your previous experience.

Only some advanced Python classes are appropriate for data science instead of development, and only some tools or skills are industry-specific. Consider the following advanced tools and how you might use them if they apply to your field.

Flask - Flask is an advanced microframework for website and web application development. While many Python pros find Django easier for comparable tasks, some feel Flask is more versatile. If you work in a field like Python development, sophisticated web app design, or microservices, consider adding Django and Flask to your skill set.

Graphical user interface (GUI) frameworks - The top considerations for any application are security, performance, and graphical user interface (GUI). Though most non-technical people understand the first two, only tech professionals know what a GUI is, much less how to build one. The graphical user interface is what your user sees and interacts with first when opening your website or application. It can consist of buttons, icons, text, and other elements. Python GUI frameworks for development pros include Tkinter, PyQt5, and PyForms, but there are many others. Consider learning some of these tools if you plan a career in Python development.

PySpark - Python data science pros who work in big data may have to use PySpark to write an Apache Spark-based program. While you can find free tutorials about using this advanced tool, it makes the most sense in an advanced Python class or on-the-job training. PySpark is one among many Python-centered libraries and frameworks.

In many intermediate to advanced Python classes, you will learn how to apply conceptual knowledge to real-world situations. Noble Desktop programs like the Data Science Certificate, FinTech Bootcamp, Software Engineering Certificate, and Data Analytics Certificate all provide intermediate and advanced training, and there is always more to learn—both on the job and in the future.