As the technology sector rapidly evolves, the importance of upskilling development teams in Python cannot be overlooked. Python is a preferred programming language for its simplicity and readability. Developers use Python in frameworks like Django and Flask to build scalable and secure web applications efficiently. Similarly, Python's libraries, such as NumPy, pandas, and TensorFlow, provide powerful tools for data analysis and visualization that give developers insights that help them make informed decisions around building models and driving innovations from data.
When L&D teams invest in Python training for upskilling, they commit to equipping their dev teams with a versatile and powerful toolkit that will enhance their problem-solving abilities and help them tackle any technological challenges. This strategic upskilling initiative can significantly impact dev teams' ability to innovate and maintain a competitive advantage in the tech sector.
Top Python courses for training programs
At DevPath, we offer a range of courses L&D teams can use to equip their dev teams with essential Python skills. The top Python courses for training programs are as follows:
Learn Functional Programming in Python
Learn Object-Oriented Programming in Python
Master Linear Programming in Python with PuLP
Mastering the Art of Programming in Python 3
Dynamic Programming in Python
Learn Functional Programming in Python
The course offers specialized content in functional programming with Python. The course is structured to provide a comprehensive understanding of functional programming, its principles, and how it can be effectively applied to Python's procedural and object-oriented features.
Starting with the basics, the course introduces a central concept in functional programming—how functions in Python can be treated as objects. Moving forward, developers learn about the importance of immutability in functional programming and how to implement recursion, which is useful for solving problems by having a function call itself. There are more advanced functional programming elements covered in the course as well, such as closures (for creating function factories and functionally maintaining state), iterables and iterators (which are crucial for efficiently traversing data), and generators (which allow developers to lazily produce values, therefore saving memory and improving performance). There are three exams that test developers' theoretical understanding of the key concepts of functional programming within Python and equip them with the skill set they need to incorporate functional programming techniques into their Python projects.
Learn Functional Programming in Python
The functional programming paradigm can be a powerful tool, especially as it can be integrated seamlessly with procedural and object-oriented code in Python. In this course, you’ll learn what functional programming is, how it’s used, and the features of Python that support it. To start, you’ll learn how functions act as objects, the role of mutability, and how to perform recursion. In the latter half of the course, you’ll focus on closures, iterables & iterators, generators, and more. Throughout the course will be three exams which will test your understanding and really drive home what you’ve learned. By the end, you’ll have a new programming paradigm to add under your belt and have the confidence to start using functional programming in your own projects.
Learn Object-Oriented Programming in Python
This course is meticulously designed to guide developers through object-oriented programming (OOP) in Python. It begins by introducing its foundational principles, such as objects and classes, which are the building blocks of OOP. The course then shows developers how to create reusable and modular code by defining classes that encapsulate data and functions related to specific entities. As developers progress through the course, they'll come to learn about inheritance, encapsulation, and polymorphism, and they will discover how Python's syntax and built-in functionalities support and enhance OOP principles to make the coding experience both efficient and enjoyable. After developers finish the course, they'll be able to write cleaner and more modular code, applying OOP principles effectively in their Python projects to build complex and high-quality software applications.
Learn Object-Oriented Programming in Python
Learn to write cleaner, more modular, and more scaleable code in Python by gaining a master of Object Oriented Programming (OOP). You'll start with the basics of object oriented programming and build up to more advanced concepts such as inheritance, information hiding, and polymorphism. Along the way you'll learn how each concept applies to Python in particular, as well as how various Python features make it particularly convenient for OOP. This course is filled with hands-on coding challenges, playgrounds, snippets, and illustrations to keep things interactive.
Master Linear Programming in Python with PuLP
Optimization is vital in enhancing application performance. As a powerful tool for linear programming of the open-source Python library, PuLP equips developers with the skills to optimize computing functions. Developers will learn to identify variables and constraints in computing functions and work with PuLP's APIs and the variety of optimizers it offers. With a strong emphasis on practical application, developers will work on common linear programming algorithms and learn how to implement them to solve real-world problems in logistics, supply chain management, and even resource allocation.
Master Linear Programming in Python with PuLP
We make optimization decisions every day. To improve the performance of your applications, computers need to do the same. This course will help you optimize computing functions through the open-source Python library PuLP. In this course, you’ll learn about linear programming, an optimization approach that maximizes or minimizes functions through defined algebra, and the PuLP library along with its various optimizers available via APIs. You’ll identify the variables and constraints of computing functions and define the optimization goals. You’ll then learn and practice common linear programming algorithms. Finally, you’ll be introduced to potential applications in the real world. By the end of the course, you will be able to optimize computing functions using Python and PuLP.
Mastering the Art of Programming in Python 3
This course is designed to elevate developers' Python skills to the next level. It's ideal for practicing Python programmers who aspire to deepen their understanding of Python 3, especially those transitioning from Python 2. The course covers Python's built-in data structures and the different programming paradigms that Python supports, such as functional programming and OOP. After that, developers will move on to more advanced topics like iterables, generators, and coroutines. These concepts are crucial for writing Python code for applications that require efficient data processing and asynchronous operations. The course also includes two hands-on projects that are designed to challenge developers and put their knowledge of theoretical concepts into practice. After the completion of this course, developers will be able to write code efficiently, elegantly, and in line with best practices.
Mastering the Art of Programming in Python 3
This highly interactive and advanced course will give you insight into the most common Python tricks and tips. This course is for practicing Python programmers who are aiming for proficiency in Python 3. If you want to switch from Python 2 to Python 3, this is your go-to course. This course will help you learn the Pythonic Way of writing code and leveraging advanced robust features to become more proficient than the average developer. You’ll start by covering Python’s built-in data structures, and then you’ll move on to different programming paradigms like functional programming and object-oriented programming. In the latter half of the course, you’ll focus on iterables, generators, and coroutines. You’ll also have the opportunity to work on two projects to help strengthen what you learn. In all, this course is perfect for anyone who wants to become a confident and competent Pythonista by picking up the idioms and practical tips.
Dynamic Programming in Python
This course lays the foundation for the key concepts of dynamic programming, such as recursion, and strategies like the top-down and the bottom-up approaches. As an essential skill to enhance algorithm efficiency, dynamic programming emphasizes the breaking down of technical problems—especially those that involve making a sequence of interrelated decisions—into smaller, manageable parts. Dynamic programming also emphasizes how these solutions can be reused to solve the larger problem, reducing the overall complexity. By the end of this course, developers will have gained a comprehensive understanding of dynamic programming and its applications in technical projects, allowing them to write more efficient and optimized algorithms.
Dynamic Programming in Python
Dynamic programming is something every developer should have in their toolkit. It allows you to optimize your algorithm with respect to time and space — a very important concept in real-world applications. In this course, you’ll start by learning the basics of recursion and work your way to more advanced DP concepts like Bottom-Up optimization. Throughout this course, you will learn various types of DP techniques for solving even the most complex problems. Each section is complete with coding challenges of varying difficulty so you can practice a wide range of problems. By the time you’ve completed this course, you will be able to utilize dynamic programming in your own projects.
Final word
All the courses we've mentioned here are designed to showcase the practical applications of Python. The courses cover all the necessary theoretical knowledge, and their hands-on projects and interactive elements—such as practical coding challenges, playgrounds for code experiments, and illustrative snippets—reinforce developer learning and aid them in applying their skills to Python projects.
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