PCEP - Certified Entry-Level Python Programmer certification is a professional credential that measures your ability to accomplish coding tasks related to the essentials of programming in the Python language. A test candidate should demonstrate sufficient knowledge of the universal concepts of computer programming, the syntax and semantics of the Python language as well as the skills in resolving typical implementation challenges with the help of the Python Standard Library.

This book is designed to help you to Pass your PCAP Exam from the 1st try, and get your Certification in the easiest way.The PCAP - Certified Associate in Python Programming certification is a professional credential that measures your ability to accomplish coding tasks related to the basics of programming in the Python language and the fundamental notions and techniques used in object-oriented programming.

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Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos Key FeaturesImplement image classification and object detection using machine learning and deep learningPerform image classification, object detection, image segmentation, and other Computer Vision tasksCrisp content with a practical approach to solving real-world problems in Computer VisionBook Description Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries. What you will learnInstall and run major Computer Vision packages within PythonApply powerful support vector machines for simple digit classificationUnderstand deep learning with TensorFlowBuild a deep learning classifier for general imagesUse LSTMs for automated image captioningRead text from real-world imagesExtract human pose data from imagesWho this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.

How do successful agile teams deliver bug-free, maintainable software—iteration after iteration? The answer is: By seamlessly combining development and testing. On such teams, the developers write testable code that enables them to verify it using various types of automated tests. This approach keeps regressions at bay and prevents “testing crunches”—which otherwise may occur near the end of an iteration—from ever happening. Writing testable code, however, is often difficult, because it requires knowledge and skills that cut across multiple disciplines. In Developer Testing, leading test expert and mentor Alexander Tarlinder presents concise, focused guidance for making new and legacy code far more testable. Tarlinder helps you answer questions like: When have I tested this enough? How many tests do I need to write? What should my tests verify? You’ll learn how to design for testability and utilize techniques like refactoring, dependency breaking, unit testing, data-driven testing, and test-driven development to achieve the highest possible confidence in your software. Through practical examples in Java, C#, Groovy, and Ruby, you’ll discover what works—and what doesn’t. You can quickly begin using Tarlinder’s technology-agnostic insights with most languages and toolsets while not getting buried in specialist details. The author helps you adapt your current programming style for testability, make a testing mindset “second nature,” improve your code, and enrich your day-to-day experience as a software professional. With this guide, you will Understand the discipline and vocabulary of testing from the developer’s standpoint Base developer tests on well-established testing techniques and best practices Recognize code constructs that impact testability Effectively name, organize, and execute unit tests Master the essentials of classic and “mockist-style” TDD Leverage test doubles with or without mocking frameworks Capture the benefits of programming by contract, even without runtime support for contracts Take control of dependencies between classes, components, layers, and tiers Handle combinatorial explosions of test cases, or scenarios requiring many similar tests Manage code duplication when it can’t be eliminated Actively maintain and improve your test suites Perform more advanced tests at the integration, system, and end-to-end levels Develop an understanding for how the organizational context influences quality assurance Establish well-balanced and effective testing strategies suitable for agile teams

The 98-381: Introduction to Programming Using Python is a Python certification from Microsoft. The certification is meant for candidates who can: Recognize the various data types in Python Understand and modify existing Python code Write syntactically correct Python code Upon successful completion of the Microsoft Python certification examination, the candidates are awarded the MTA (Microsoft Technical Associate) credential. An MTA 98-391 certified individual can work with Python on a professional level and is ready to explore the advanced aspects of the high-level, general-purpose programming language and related technologies. Exam Details Name – Introduction to Programming Using Python Code – 98-381 Duration – 45 minutes Language(s) – Chinese (Simplified), Chinese (Traditional), English, French, German, Japanese, Korean, Portuguese (Brazil), and Spanish Level – Associate Passing Percentage – 70% Prerequisites – 100+ hours of instruction/hands-on experience in the Python programming language, familiarity with the capabilities and features of Python, ability to understand, write, debug, and maintain well documented Python code Price – $127 Total Questions – 40 Type – Drag & drop, a selection from the drop-down list, single-choice and multiple-choice questions Syllabus Data and data type operations Document and structure code Error handling Input and output operations Python conditional statements and looping Python modules and tools Now that you know what the best certifications are, it’s time to prepare for them. How to do that? You need to go through the syllabus, practice, read as much as possible about Python, and much more. You can, however, also take Python certification practice tests to ensure that you’re certification-ready without overindulging yourself in preparation for clearing the Python certification exam.

PCEP – Certified Entry-Level Python Programmer Certification is a comprehensive mock exam with emphasis on using the PCEP 30-01 Syllabus as guide on the question topic. The audience should be at least a beginner Python programmer or have a good grasp on programming because this is not a tutorial. All questions are tested and have undergone quality control. All questions are based on individual topics and all topics have been covered. Some of the topics may not be thoroughly covered but each and every topic in the syllabus have a corresponding question with sufficient representation. Exam block #1: Basic Concepts Objectives covered by the block (9 exam items) fundamental concepts: interpreting and the interpreter, compilation and the compiler, language elements, lexis, syntax and semantics, Python keywords, instructions, indenting literals: Boolean, integer, floating-point numbers, scientific notation, strings comments the print() function the input() function numeral systems (binary, octal, decimal, hexadecimal) numeric operators: ** * / % // + – string operators: * + assignments and shortcut operators Exam block #2: Data Types, Evaluations, and Basic I/O Operations Objectives covered by the block (11 exam items) operators: unary and binary, priorities and binding bitwise operators: ~ & ^ | << >> Boolean operators: not and or Boolean expressions relational operators ( == != > >= < <= ), building complex Boolean expressions accuracy of floating-point numbers basic input and output operations using the input(), print(), int(), float(), str(), len() functions formatting print() output with end= and sep= arguments type casting basic calculations simple strings: constructing, assigning, indexing, immutability Exam block #3: Control Flow – loops and conditional blocks Objectives covered by the block (8 exam items) conditional statements: if, if-else, if-elif, if-elif-else multiple conditional statements the pass instruction building loops: while, for, range(), in iterating through sequences expanding loops: while-else, for-else nesting loops and conditional statements controlling loop execution: break, continue Exam block #4: Data Collections – Lists, Tuples, and Dictionaries Objectives covered by the block (7 exam items) simple lists: constructing vectors, indexing and slicing, the len() function lists in detail: indexing, slicing, basic methods (append(), insert(), index()) and functions (len(), sorted(), etc.), del instruction, iterating lists with the for loop, initializing, in and not in operators, list comprehension, copying and cloning lists in lists: matrices and cubes tuples: indexing, slicing, building, immutability tuples vs. lists: similarities and differences, lists inside tuples and tuples inside lists dictionaries: building, indexing, adding and removing keys, iterating through dictionaries as well as their keys and values, checking key existence, keys(), items() and values() methods strings in detail: escaping using the \ character, quotes and apostrophes inside strings, multi-line strings, basic string functions. Exam block #5: Functions Objectives covered by the block (9 exam items) defining and invoking your own functions and generators return and yield keywords, returning results, the None keyword, recursion parameters vs. arguments, positional keyword and mixed argument passing, default parameter values converting generator objects into lists using the list() function name scopes, name hiding (shadowing), the global keyword Questions in the Practice tests are much more difficult than what is included in the Certified Entry-Level Python Programmer Certification. I recommend doing hands-on to test the validity of the answers and emphasize on the importance of coding different permutations and combinations on the examples given. All questions are self-explanatory and it will be easier to understand if the code is run on IDLE or the user's preferred Python IDE.