Training Success Elements

  • A pre-enrollment assessment identifies the right candidates for the training program.
  • Hundreds of AI-tutelaged mini projects build competency and confidence.
  • Realtime AI-based contextual assistance is available, throughout the training.
  • Training is competency-based so each topic needs to be mastered before going on.
  • Trainees are Python Programming Subject Matter Experts, at graduation.

Overview of Training

This cornerstone training program is designed for individuals who are determined to become highly skilled Python Programmers. It provides them with enough Python coding practice to make them highly skilled and enough theoretical knowledge to pass the Python Institute’s industry-recognized PCEP certification exam. 

Python programming can’t be learned in a few weeks by passively watching video tutorials and then doing some unassisted coding assignments. 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 trainees’ learning, they are assisted by an engaging Artificial Intelligence-based teaching platform that watches their every step, grading their work in real time, and helping them with contextual information, hints, and templates, as needed. The AI-based platform also teaches them best practices which includes conventions for writing readable and consistent code. 

They learn actively from Day 1, using Python to solve very simple tasks. After gaining confidence in one topic, they move to the next one. The progression has been constantly improved and tuned for many years, and it is so smooth that they never get lost. And, they are never alone.

Trainees 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 them with the coursework, when needed. Trainee are each assigned a personal coach who prepares a personalized roadmap and training timeline with them, and then works with them on a weekly basis for the entire duration of the training. 

The Python Developer career training program takes an estimated 320 hands-on hours to complete.



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 their coach, it is determined that enrollees need a basic middle school level math refresher, our optional Workplace Math course provides hands-on review and practice to bring them up to speed.

With an appropriate math foundation in place, they proceed to Computational Literacy. This course is waived if they 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, trainees write programs in simplified Python syntax for a virtual robot to solve various tasks. In this way, they learn how to design algorithms and type code, identify repeating patterns, and use loops to repeat commands and sequences of commands. They 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, they 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 trainees in an excellent position to start learning Python.

Trainees’ actual Python training then begins with Introduction to Python. This course provides a detailed and comprehensive overview of the Python programming language; they learn Python by solving programming problems of gradually increasing complexity, using simple calculations, loops, conditions, local and global variables, functions, exceptions, and recursion. They also become proficient in working with fundamental Python data structures, including tuples, lists, and dictionaries. Throughout the course, they 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, trainees 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, trainees learn how to use the powerful Python library Matplotlib for plotting and drawing.

At this time, trainees are ready to embark on Software Project 1, where they build their 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 trainees with a valuable insight into the principles of good software design.

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

In Software Project 2, trainees build their 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 trainees 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 trainees how to visualize data in the form of simple graphs, bar charts, pie charts, color maps, surface plots, wireframe plots, and contour plots. They 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 trainees 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 they 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 trainees to score high on the PCEP exam. PCEP is an industry-recognized certification from the Python Institute that adds a significant weight to their resume. They are encouraged to take the PCEP exam before starting to work on their Capstone Project.

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

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

In both cases, trainees are required to create a free Github user account, and to install a Python IDE on their own computer or laptop (we’ll help them 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 trainees are taught and what they are required to make use of themselves. To you, this means that graduates 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 trainees are expected to master.


Advanced Python Developer Training

Upon completing the Python Developer Training, graduates can 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 them for the Python Institute’s PCAP exam. More information is available upon request.


Developing Soft Skills

At the same time as trainees develop Python Programming hard skills, coaches develop their soft skills. Those 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 trainees throughout their training, helping them do mini projects in realtime and providing them a feeling of accomplishment as they complete each mini project.


Get More Information

To talk with one of our product specialists about what this training program could do for you, schedule a call below, fill in the Get-In-Touch form, or simply use the CHAT BOX at the bottom right of this screen.