Nov
18

Part 1: Finding the Answers On Your Own

INE’s on-demand Data Science courses are far easier on your budget than those of a conventional coding bootcamp, let alone an accredited computer science degree. Like other technical career preparation courses, you’ll get plenty of opportunities to practice. There’s no other way to become a professional. 

In a more expensive course, you might have an instructor or a teaching assistant whose office hours you can visit when you’re stuck. Your instructor might also give you a professional reference for your first technical job. However, after a certain point, there is only so much hand-holding you will have. At some point, you are the one expected to lead your teammates on the job, and no one is there for you. You’ll need to learn how to rely on other resources, so why not save the money and be more independent from the start? 

Data Science Starts with Preparation

The first thing you need to do, probably before you write a line of code, is learn to read the Python documentation and the textbooks. Familiarity with the documentation can give you a feel for how to write Python and what the language will and will not do. The core Python language, which is the programming language used for the INE course, has extensive official documentation and tutorials. So do the specialized Data Science and other Python libraries taught in the course, such as NumPy and pandas.

A programming library is a reusable set of programming commands, with a defined interface to enable this set of commands to be used in a program. The core Python language is available in all Python programs, and other libraries can be specially added. 

Utilize Search Engines

Now here’s a mini-exercise. Can you find the documentation of the latest stable versions of the core Python language and of the two libraries mentioned here, NumPy and pandas? Hint: Search engines are your friend. The answer to this exercise is given at the end of this blog post.

When your code does not work, another tip is to read the error messages you receive. Part of your error message should be common to a variety of other error messages, and part should be a distinct phrase. Take the part that is distinct and copy/paste it into a search engine. You might want to put it in quotes, to search for the consecutive phrase rather than the non-consecutive words. This will hone your search down to web pages where your specific error, and its fix, is discussed. Sometimes these web pages do not have a fix, but have clues you can also search for. Tracing the clues is part of learning how to code.

Pinpoint the Cause of Any Problems

The program may also not give an explicit error, but may still not be behaving how you want. You need to think about the problem line of code by line of code, to pinpoint the specific commands you will need to change. One of the first programming commands you will learn is how to print out lines of text onto your screen. Add these commands to the program, after each line or so, to verify the lines of code in your program are running the correct number of times.

In Python, you may also be creating something called a variable. A variable is a value stored in a specific location in memory and given a name. When you refer to the name of the variable, you can access its value. Variables are very important in most programs for storing and sharing information. And as you run the program, you can specify how the variable’s value changes. When you test your program by printing out the line of code, you can include the value of the variable to double-check that this value has changed to what you want.

Python also offers standard tools, such as pdb, to debug - which means fix - your code using a similar approach. Another exercise, with the answer given at the end of this post, is to find the documentation of pdb. Using these types of print and debug commands will give you a fine-scale view of how your program is working. Once you have fixed your program’s issues, removing the lines of code used for debugging is one step in cleaning up your code.

Don’t Give Up

If you want to overcome most programming obstacles, you need practice. Even so, you can be stuck for hours or days at times, unable to figure out how to fix an issue with your program. This struggle is normal. It is part of learning to code. Just make sure you set aside a good bloc of coding time at least a few days a week, ideally in a routine, and eliminate distractions. Even with a designated course instructor, you will probably face this type of struggle and you should first extensively try the methods described above. It is important to get efficient at searching for the issue yourself, even if this feels painful and cumbersome at first.

Taking a self-paced online course such as INE’s definitely requires an extra dose of personal discipline. From time to time, you may well need someone else to give you that extra pair of eyes or even that extra bit of accountability. And sometimes, coding is actually lonely. Perhaps you need more human interaction than this post describes. As an INE student, there are still many ways to get it. The next post discusses how to get this crucial feedback without a bootcamp-provided instructor, and what you can learn.

Ready to discover what INE's Data Science courses can do for you? Create your free Starter Pass Account today.

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Answers to exercises:

The documentation of the latest stable version of core Python is at https://docs.python.org/3/. INE uses Python 3.6, documented at https://docs.python.org/3.6/. Code is written slightly differently in different Python versions.

The documentation of the latest NumPy version is at https://numpy.org/doc/stable/.

The documentation of the latest Pandas version is at https://pandas.pydata.org/pandas-docs/stable/.

The documentation of the Python debugger pdb is at https://docs.python.org/3/library/pdb.html.



Rebecca Sealfon
About Rebecca Sealfon

Rebecca Sealfon is a RecruitLoop Top 50 NYC female full-stack software engineer. Her career in software engineering, data science, and technology instruction includes a stint as a software engineer at Google. Rebecca maintains forums about technology, science, and geopolitics on Quora.com that have received millions of views and has published articles in the New York Daily News, Smithsonian magazine, and the Daily Beast. Follow her on Quora and on Medium.

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