|
via Udemy |
Go to Course: https://www.udemy.com/course/python-course-1/
Certainly! Here's a comprehensive review and recommendation for the beginner Python course on Coursera: --- **Course Review and Recommendation: Beginner Python Programming on Coursera** If you're new to programming and eager to start your coding journey, this beginner Python course on Coursera is an exceptional choice. Designed specifically for individuals with little to no prior experience, the course provides a thorough and accessible introduction to Python, one of the most popular and versatile programming languages. **Course Content and Structure** The course covers a wide array of fundamental topics, starting with the basics such as installation, setting up the development environment, and writing your first Python program. It then progresses into core programming concepts like data types, variables, control flow, functions, and data structures. The curriculum is carefully structured to build your confidence step-by-step, ensuring you grasp essential concepts before moving on to more advanced topics such as object-oriented programming, file handling, modules, and error debugging. One of the most standout features is the emphasis on Python's simplicity and readability, which makes learning programming much less daunting for beginners. The practical approach of learning through experiments and exercises allows students to immediately apply what they've learned in real-world scenarios, such as data manipulation, automation, and basic web development. **Skills You Will Gain** By completing this course, you'll be able to: - Write and run basic to intermediate Python scripts - Understand Python syntax and semantics - Manipulate data using lists, tuples, dictionaries, and strings - Control program flow with conditional statements and loops - Develop functions and understand the concepts of scope and recursion - Work with files and create simple data analysis workflows - Grasp the fundamentals of object-oriented programming - Develop simple web applications using Flask - Handle errors and debug code effectively The course also touches on more specialized topics such as data analysis with libraries like pandas and matplotlib, working with databases, and an introduction to machine learning concepts, adding tremendous value for learners interested in data science or software development. **Strengths** - Well-structured for absolute beginners - Clear explanations with practical exercises - Extensive coverage of core Python concepts and tools - Includes advanced topics for further exploration - Access to a supportive community and instructor feedback **Areas for Improvement** While the course is comprehensive, learners with a specific focus on web development or data science may need supplementary courses to reach proficiency. Also, some sections, such as machine learning and web development, are introductory and might require additional self-study or specialized courses for mastery. **Conclusion and Recommendation** This beginner Python course on Coursera is highly recommended for aspiring programmers, students, or professionals seeking a solid foundation in Python. Its combination of theoretical understanding and hands-on practice makes it ideal as a starting point in your programming career. Whether you're interested in automating tasks, exploring data science, or developing web applications, this course provides the essential skills you'll need to advance further. Enroll today to begin your journey into the world of programming with confidence and a strong foundational knowledge of Python! --- Please let me know if you'd like a more condensed review or tailored to specific interests within Python!
This beginner Python course is a comprehensive introduction to the world of programming using the Python programming language. This course is designed for individuals with little to no prior coding experience, making it an ideal starting point for those looking to embark on a journey into the world of computer programming.Throughout the course, students are introduced to the fundamental concepts of programming, including variables, data types, and basic operations. They learn how to write and execute simple Python programs, gaining hands-on experience in solving real-world problems using code.One of the key highlights of the course is the emphasis on Python's simplicity and readability. Python's clean and intuitive syntax makes it an excellent choice for beginners, enabling them to focus on problem-solving rather than grappling with complex syntax rules.As the course progresses, students delve into more advanced topics, such as conditional statements, loops, and functions. They learn how to control the flow of their programs, allowing them to create more sophisticated and interactive applications.Data manipulation is another critical aspect covered in the course. Students learn how to work with lists, tuples, dictionaries, and strings, enabling them to store, retrieve, and manipulate data efficiently. This knowledge forms the foundation for more advanced data science and software development concepts.By the end of the course, students are equipped with the skills to tackle real-world programming challenges. They can create basic applications, automate repetitive tasks, and have a solid understanding of the Python ecosystem. This beginner Python course serves as a stepping stone for those interested in pursuing careers in software development, data analysis, or any field that requires programming skills. It opens doors to a wide range of opportunities in the ever-evolving tech industry and provides a strong foundation for further learning and specialization in Python and other programming languages.Topics: An introduction to Python and an overview of programming languages.Introduction to Python and its featuresSetting up Python environment (interpreter, IDE)How to write and run your first Python programAn introduction to Python's basic syntax and variables.Python command linePython commentsgetting inputstring to integer conversionlist comprehensionexception handlingpolymorphismdebugginginstalling pyinstallerthe range functionData Types and OperatorsNumeric data types: int, float, complexStrings and string manipulationstrings and boolean type variablesstringsBoolean data type and logical operatorsBasic arithmetic, comparison, and assignment operatorsType conversion and type castingchanging types of variablesControl FlowConditional statements: if, elif, elseif elif elseUsing logical operators with conditionalswhile loop and listLooping constructs: while loop, for loopIterating over sequences (lists, strings, tuples)Using break and continue statementsData Structures Part IUnderstanding lists and tuplesLists: creation, indexing, slicing, appending, and extendingAccessing elements in a listList methods and operationsList manipulationlists, tuples and dictionariesTuples: creation, accessing elements, immutabilityTuple immutabilitySets: creation, operations, and methodsUsing list comprehensionsData Structures Part IIDictionaries: creation, accessing elements, dictionary methodsNested data structuresCombining data structures for complex data organizationIntroduction to mutability and immutabilityFunctionsDefining and calling functionsFunction parameters and argumentsReturn statements and returning valuesScope of variables: global vs localUnordered List Item Recursion: concept and examplesIntroduction to Object-Oriented Programming (OOP)Understanding objects and classesDefining classes and creating objectsClass attributes and methodsInstance attributes and methodsInheritance and polymorphism basicsFile Handling and ModulesOpening, reading, writing, and closing filesFile Manipulation 1File Manipulation videoFile modes and file objectsWorking with different file formats (text files, CSV, JSON)Creating and using modulesUnderstanding modules and importing them 2Creating and using packagesExploring the Python Standard LibraryImporting modules and packagesError Handling and DebuggingUnderstanding exceptions and errorsUsing try-except blocks for error handlingRaising exceptionsDebugging techniques and toolsBest practices for writing clean and debuggable codeReflection and feedback on the courseNetworkingNetworking Foundations with Pythondata analysisinstalling pandasplotting with matplotlibPlanning, designing, and implementing a Python applicationhandling missing datastandardizationhow to plot a bar charthow to plot a scatter bar and line charthow to make a pie chartbox charthistogramheatmapviolin graphspythonic and pandas descriptionnumpy scipy hdf5 matplotlibjupyterpytable hdfspymongosqlalchemy, redis, pymysql, scikit-learntensorflowkerasseaborn, plotlyhow to install jupyter on linuxHow to install python data analysis libraries in Windows.numpy arraysnumpy array indexpandas read csv into a data framepytables installingpytables hdf5: how to install vitablesseaborn examplesseaborn examples ( video )bokehbokeh videoDaskweb development in pythonWhat is flask ( Article )what is flask ( Video )Introduction to Flask frameworkstarting flaskCreating web applications with flaskJSON (JavaScript Object Notation)Flask-SQLAlchemyFlask-MongoEngineFlask-PyMongoFlask-WTFCSRFWTFormsDjangoCross-Site Scripting (XSS)Model-View-Controller (MVC)Web application firewalls (WAFs)Content Security Policy (CSP)The Open Web Application Security Project (OWASP)Document Object Model (DOM)DOM-based XSSDon't Repeat Yourself (DRY)InternationalizationLocalizationFlask-LoginFlask-AdminGunicornuWSGIscipyscipy constantsscipy constants part 2scipy constants weights and minutestensorflowstarting tensorflowTensorflow examplesSpecial casesWorking with PDF files in pythonIntegrating payment gateways with pythonMachine learningLight GBMOpenAI GymXGBoostHugging Face TransformersCatBoostPyTorchGenerative AIGLM PyTorchPyroNeRFStyleGANSoftware developmentMaking the programmer sweatDatabasesMongoDBNoSQLDatabase Interaction with SQLAlchemyOverview of SQLAlchemyORM conceptsCRUD operationsCommercial packagesRouting and viewsAnaconda distributionDevelopment toolsPyCharmPylintFlake8Visual Studio Code (VS Code)JetBrainsIntelliJ IDEACondaGitMercurialSubversionDifference between Conda and AnacondaMypyPIPPython Package Index (PyPI)Python Packaging Metadata (PEP 566)Python Package Index Metadata (PEP 503)Python Software Foundation (PSF)Python Enhancement Proposals (PEPs)