Overview of Training

This cornerstone training program is designed for you if you are determined to become a skilled Python Developer and a respected member of a modern software development team. It provides you with enough Python coding practice to make you job-ready and enough theoretical knowledge to pass the Python Institute's Certified Entry-Level Python Programmer (PCEP) exam. It also teaches you the soft skills employers look for in job applicants. Upon completing the training, you are ready to start a successful new career in Python software development.

Python programming can’t be learned in a few weeks by passively watching video tutorials and then doing some coding exercises on your own. It is an advanced skill set which can only be mastered with a significant amount of closely supervised practice. NCLab’s proven training method is called Instructor-Assisted Learning By Doing.

Throughout your learning, you are assisted by a powerful Artificial Intelligence-based teaching platform that watches your every step, grading your work in real time, and helping you with contextual information, hints, and templates, as needed. The AI-based platform also teaches you best practices which includes conventions for writing readable and consistent code. Finally, you also have access to our highly responsive instructional support team that is composed of Python coding professionals, college instructors, and former NCLab trainees who promptly assist you with the coursework, when needed.

You learn actively from Day 1, using Python to solve very simple tasks. After gaining confidence in one topic, you move to the next one. The progression has been constantly improved and tuned for many years, and it is so smooth that you never get lost. And, you are never alone. The Python Developer career training program takes an estimated 320 hands-on hours to complete. You are assigned an academic adviser who prepares a personalized roadmap and training timeline for you, and then works with you for the entire duration of the training. Because your training is self-paced and individualized to your schedule, you are able to build a consistent training routine with your academic adviser that does not interfere with your work and family commitments.

Coursework

To begin with, Python is used to solve real-life problems, therefore Python developers must know a limited amount of math. If in consultation with your academic adviser, it is determined that you need a basic middle school level math refresher, our optional Workplace Math course provides hands-on review and practice to bring you up to speed.

With an appropriate math foundation in place, you proceed to Computational Literacy. This course is waived if you have significant prior computer programming experience, but many experienced programmers like to take it anyway, as a refresher. This course teaches computational thinking which is the most important skill in computer programming.

In this visual course, you write programs in simplified Python syntax for a virtual robot to solve various tasks. In this way, you learn how to design algorithms and type code, identify repeating patterns, and use loops to repeat commands and sequences of commands. You also learn Boolean logic, conditional statements, conditional loops, how to define custom commands and functions, and how to break complex problems into simpler ones. Finally, you learn how to use recursion and stochastic algorithms (algorithms that involve randomness) to solve tasks that would be very difficult or impossible to solve otherwise. Taking this course puts you in an excellent position to start learning Python.

Your actual Python training then begins with Introduction to Python. This course provides a detailed and comprehensive overview of the Python programming language. You learn Python by solving programming problems of gradually increasing complexity, using simple calculations, loops, conditions, local and global variables, functions, exceptions, and recursion. You also become proficient in working with fundamental Python data structures, including tuples, lists, and dictionaries. Throughout the course, you are developing a good Python coding style and other good coding habits.

More than 80% of work computers do is processing text. Therefore, in the course Working With Text, you learn how to process, analyze, and manipulate text strings with Python.

Python is known for its powerful graphic capabilities. In the course Plotting and Drawing, you learn how to use the powerful Python library Matplotlib for plotting and drawing.

At this time, you are ready to embark on Software Project 1, where you build your own Graphics Editor, based on Matplotlib. The Graphics Editor is able to create shapes such as squares, triangles, rectangles and circles, fill objects with color, move, scale and rotate shapes, and combine them to make complex drawings. In addition to substantial programming practice, this Software Project provides you with a valuable insight into the principles of good software design.

Most data is stored in files. Therefore, the course Working with Files teaches you how to open files, read data from them, process the data, and write to files.

In Software Project 2 you build your own Image Viewer in Python. The Image Viewer is able to read bitmap images from files, store them as 2D Numpy arrays, and visualize them with Matplotlib. In this Software Project you practice working with files, text strings, and the Numpy and Matplotlib libraries.

The world we live in is driven by data. Therefore, the course Data Visualization with Python teaches you how to visualize data in the form of simple graphs, bar charts, pie charts, color maps, surface plots, wireframe plots, and contour plots. You also learn how to visualize data on 2D Cartesian grids and unstructured triangulations.

Most real-life applications of Python are to some extent related to Data Analytics (DA). Therefore, the DA Minimum course teaches you how to use the Pandas library and perform elementary Data Analytics with Python.

Every Python developer must know the basics of Computer Science (CS) including the binary, octal, and hexadecimal numeral systems. These are also required for the PCEP exam. That’s exactly what you learn in the course CS Minimum.

The Intermediate Topics in Python course covers remaining topics which are required for the PCEP exam. These include variadic functions, anonymous (lambda) functions, built-in functions any(), all(), map(), filter(), reduce(), eval() and exec(), iterables and iterators, and generator functions and generator expressions. Students also gain a deeper insight into mutability, shallow and deep copying, and exceptions handling.

The PCEP Prep course includes several PCEP practice exams and prepares you to score high on the PCEP exam. PCEP is an industry-recognized certification from the Python Institute that will add a significant weight to your resume. You are encouraged to take the PCEP exam before starting to work on your Capstone Project.

Finally, you complete a Capstone Project where you choose one of two options:

• Option 1: Look up open source projects on Github, find one that you like, and contribute to it by submitting a pull request. Your contribution must be consulted and approved by your NCLab instructor in advance.
• Option 2: Implement your own program in Python and upload it to Github. The topic of your program is chosen by you, but must be consulted and approved by your NCLab instructor in advance. Typically, a more substantial program is required compared to Option 1.

In both cases you are required to create a free Github user account, and to install a Python IDE on your own computer or laptop (we'll help you with that).

Program Syllabus

We invite you to look at our training program syllabus but we need to explain how it is different from other syllabi you might have or will look at.

While all syllabi show you what is taught in the training, our syllabus shows you both what you are taught and what you are required to make use of yourself. To an employer, this means that you have actually mastered each of the topics covered. Click here to access the syllabus and use the links in the table of contents to see how the various topics that you will be expected to master.

Advanced Python Developer Training

Upon completing the Python Developer Training, you can either get a job as an entry-level Python developer or continue by taking a follow-up Advanced Python Developer Training. This training program includes object-oriented programming, event-driven programming, advanced topics in Python, and a PCAP Prep Course that prepares you for the Python Institute's PCAP exam. More information is available upon request.

Developing Soft Skills

At the same time as you develop Python programming (hard) skills, you also develop soft skills during your academic advice sessions and during your communications with your instructional support team that employers put a major emphasis on. These include professional communication, attention to detail, time management, critical and logical thinking, problem solving, perseverance, and adaptability, among others.

Experience NCLab’s Learn-By-Doing — You’ll Love It.

Click here to see how NCLab’s AI-based teaching platform is with you throughout your training, helping you do mini projects in realtime and providing you a feeling of accomplishment as you complete each mini project.

What Our Trainees Say About Us

I love going to work every day!

“Thank you for giving me the competency and confidence that I needed to get a dream job. With my limited formal education, I had serious doubts that I could master SQL and Python but learning by doing worked perfectly.” G.K.

Perfect teaching method

“As an adult with a busy schedule and the need to work around banking business hours etc.: this method of teaching is perfect for me and I would recommend it for basically anyone on any subject.” F. V.

Superb way to learn

“I really enjoyed the self-paced format of this training program. The material was presented clearly and concisely and allowed me to focus longer on concepts that were difficult, while glancing over concepts I was already familiar with.” A.C.

This is how I like to learn

“This is how I like to learn, at my own pace. I like the bite-sized tutorials and I feel a real sense of accomplishment when I complete the exercises that follow them.” M.J.

Great training!

“I watched videos, read short tutorials, viewed examples, ran demo programs, and then performed exercises that demonstrated my comprehension of the subject matter.” S.L.

The training is really great!

“Not easy but really informative. Practical experience was what I wanted and I feel that I got it.” F. Z.

The program is great

“I cannot compliment enough any training that involves students actually working on the problems rather than just listening.” A. S.

Compliments to the NCLab team

“Please extend my compliments to the NCLab team if you can, and keep advocating for this type of learning, if at the very least as an option for people like me who learn well this way.” F. A.

I’m really enjoying this class

“The emphasis on working at your own pace removes the stress of a normal class, and I can work around my other classes. NCLab is much better than similar programs, such as DataCamp. Not only do I learn the material, I retain it. Each lesson uses all or most of the previous concepts, which provides additional practice and ensures that you don’t forget the previous material. This is one of the most enjoyable and informative programs I’ve taken.” N. L.

It’s working well

“It might sound weird, but I feel as though it teaches the right parts for Python. When I was learning Python before, there were a lot of steps that felt skipped but are explained now.” P.T.

I am thoroughly enjoying the training

“I feel like I am learning a skill, much more than I felt in other courses. The use of repetition, doing programming in pieces, and the entire way the platform is laid out are far superior to how my university teaches their main, introductory, programming courses. It is too bad that the philosophy of academia is standing in its own way.” K.L.

I love it!

“I feel like I am actually LEARNING how to program, and the chunking method of the material is wonderful.” D.A.

Yes!!

“I am really enjoying this course and learning python and I also like the way that it teaches the material. I’m very glad I took this course!” R. B.

Large amount of Python programming practice

“I really enjoyed and found the Python Fundamentals and Advanced Python courses incredibly useful. In fact, the large amount of Python programming practice questions in both courses helped me obtain my summer software development internship at Pfizer by preparing me for a variety of programming interview questions.” F. F.

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