Programming Courses
Choose a course that suits your goals - from the basics to advanced skills in programming languages.
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.NET with C#ARIMA ModelingAccess Modifiers and PackagesAdvanced ARIMA TechniquesAdvanced JavaScript ProgrammingAdvanced TypeScript FeaturesAlgorithm DesignAnomaly DetectionAnomaly detection evaluation Applying RNNs to NLP tasks (sentiment analysis) Array ManipulationArray Operations and Iteration TechniquesArray Searching and FilteringArrow Function TypingArrow functions and modern syntax Artificial immune systemsAsync/Await SyntaxAsynchronous Error ManagementAsynchronous JavaScriptAsynchronous Programming in JavaScriptAutomated Search with scikit-learnBackend DevelopmentBayes' TheoremBayesian OptimizationBest Practices for Multithreaded CodeBest Practices for Non-blocking CodeC# Generics and ReflectionC# Object-Oriented ProgrammingC# Programming BasicsC++ Advanced ProgrammingC++ Conditional StatementsC++ Data TypesC++ FunctionsC++ LoopsC++ Object-Oriented ProgrammingC++ PointersC++ Programming BasicsC++ Smart PointersCRUD OperationsCallback TypingCatBoost ModelingCategorical Feature HandlingClass InheritanceClassification metrics (Accuracy, Precision, Recall, F1, ROC–AUC) Clean Code PracticesClean DOM PracticesClustering evaluation (Silhouette, Davies–Bouldin, Calinski–Harabasz) Clustering fundamentals and algorithms Code EfficiencyCode OrganizationCoefficient VisualizationComparison and Logical OperatorsComplex TypesContent and Attribute ManipulationControl FlowConvolutional Neural NetworksCorrelation AnalysisCreating and Running Threads Cross-validation techniquesCustom Error CreationCustom Validation RulesDBSCAN: noise handling and irregular shapes DOM FundamentalsDOM ManipulationDOM Manipulation and Event HandlingDart DevelopmentDart ProgrammingData Aggregation with pandasData Analysis FoundationsData CleaningData Cleaning Data HandlingData Indexing and Selection in pandasData ManipulationData PreprocessingData StorytellingData TransformationData Transformation Data VisualizationData Visualization TechniquesData Visualization with matplotlib and seabornData normalization and distance metrics Database ManagementDatabase ModelingDatabase NormalizationDate CalculationsDate Component ManipulationDate FormattingDebuggingDebugging JavaScriptDecorator UsageDeployment Best PracticesDescriptive StatisticsDesign Principles in JavaDesktop Development with .NETDiffusion Models Dimensionality reduction evaluation Dynamic StylingES6 SyntaxElement Creation and RemovalElement SelectionEncapsulation in JavaScriptEnd-to-end model development and evaluationError HandlingError Handling in Async CodeEvaluation Metrics for Generative AIEvent DelegationEvent HandlingEvolutionary optimization Experiment Tracking with MLflowExploratory Data AnalysisFeature Encoding Feature Engineering Feature Scaling Feature Selection Feature Selection MethodsFile HandlingFine-tuning Pre-trained ModelsForecast Evaluation MetricsForm Validation with TypesFront-EndFunction OverloadingFunctional Programming in JavaFunctional Programming in Python (Python Functions)Functions & SetsGANs Gaussian Mixture Models: probabilistic clusteringGenerative AI Genetic algorithms GoLang ProgrammingGradient Descent HTML5 ValidationHandling missing and categorical data Hierarchical clustering and dendrograms Hyperparameter TuningHyperparameter Tuning FundamentalsImage Processing with OpenCVImplementing recurrent networks in PyTorchInline Error MessagingIntegrals JSON Parsing and StringifyingJSON StructureJava Coding PrinciplesJava Data ManipulationJava Data StructuresJava ProgrammingJava Programming BasicsJava Thread Basics JavaScript Array MethodsJavaScript ClassesJavaScript ConditionalsJavaScript Data TypesJavaScript Date BasicsJavaScript Design PatternsJavaScript Error HandlingJavaScript Event HandlingJavaScript Form ValidationJavaScript LoopsJavaScript Object Manipulation and StructuringJavaScript ObjectsJavaScript Programming FundamentalsJavaScript Testing FundamentalsJavaScript functions Jest BasicsK-Means: principles and cluster optimization Keyboard and Mouse EventsL1, L2, and Elastic Net RegularizationLightGBM ModelingLimits & Derivatives Linear Regression with PythonLinear Transformations Logical ThinkingLogistic RegressionMLOps FundamentalsMachine Learning with scikit-learnManual Search MethodsMatlab Advanced TechniquesMatlab BasicsMatlab Conditional StatementsMatlab LoopsMatlab MatricesMatlab Modular ProgrammingMatlab VisualizationMatrix Decomposition Memory ManagmentMissing Value Imputation Mocking and Spying FunctionsModel BlendingModel Deployment with FastAPI and DockerModel Evaluation and GeneralizationModel InterpretationModel Monitoring and CI/CDModel RegularizationModel Training and EvaluationModern Date LibrariesModule and Package ManagementMultivariate AnalysisNeural NetworksNeuroevolutionNull Safety in DOM ManipulationNumPy Advanced TechniquesNumPy BasicsNumPy FunctionsObject CompositionObject Creation and ManipulationObject Detection ApproachesObject HandlingObject-Oriented ProgrammingObject-Oriented Programming ConceptsOptional and Default ParametersOutlier Detection Overfitting and RegularizationPHP Programming BasicsPandas Data ManipulationParallel StreamsParameters and return values Particle swarm optimizationPersistent Data Storage in BrowserPipeline Automation with AirflowPipeline BuildingPipeline ConstructionPrimitive TypesPrimitive vs Reference TypesProbability DistributionsProbability Rules Problem Solving with PatternsProblem-SolvingProcessing time series and sequential dataPromise Chaining and CombinatorsProperty DescriptorsPrototypal InheritancePrototype ChainPyTorch BasicsPytestPython BasicsPython Classification ModelsPython Conditional StatementsPython Data ManipulationPython Data StructuresPython Data TypesPython Function ArgumentsPython FunctionsPython LoopsPython Packing and UnpackingPython ProgrammingPython VisualizationPython Visualization with MatplotlibR Data StructuresR Programming FundamentalsRegex in ValidationRegression metrics (MSE, RMSE, MAE, R²) Rest ParametersReusable Code StructuresReusable Type PatternsReusable and modular code patternsSQL BasicsSQL in Python ProjectsScalable Type DesignSeaborn VisualizationSeries Analysis Software Architecture FundamentalsSorting and Flattening ArraysSpecial TypesStatistical Measures Statistics with PythonSwarm intelligenceTensorFlow BasicsTest-Driven Development MindsetTesting Asynchronous CodeThreading in C#Time Series AnalysisTime Zones and UTC HandlingTransfer Learning FundamentalsTransfer Learning in CVTransfer Learning in NLPTransformers Type AssertionsType ConversionType InferenceType NarrowingType SafetyType Safety in JavaScript ProjectsType-Safe Event HandlingTypeScript BasicsTypeScript Best PracticesTypeScript DOM TypingTypeScript Function TypingTypeScript FundamentalsTypeScript GenericsTypeScript Generics for DOMTypeScript InterfacesTypeScript Migration StrategiesTypeScript SyntaxTypeScript ToolingTypeScript Type SystemTypeScript TypesUI InteractivityUnderstanding RNNs, LSTMs, and GRUsUnderstanding the Event LoopUnderstanding this in FunctionsUnion and Intersection TypesUnittestUsing CallbacksVAEs Variable Relationship AnalysisVariable Scope ManagementVariable scope and local context Vectors & Matrices Web API DevelopmentWeb Scraping with PythonWeb Technology FoundationWebsite DevelopmentWorking with PromisesWriting Unit TestsXGBoost ModelinglocalStorage UsagesessionStorage Usage
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Browse Programming Languages courses and projects
2 hours
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1 hour 16 chapters
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Level
Type of lesson
Technologies
course
JavaScript Form Validation
2 hours 18 chaptersBeginner
1 STUDYING NOW
Acquired skills: JavaScript Form Validation, HTML5 Validation, Custom Validation Rules, Regex in Validation, Inline Error Messaging
course
MLOps Foundations
1 hour 16 chaptersBeginner
1 STUDYING NOW
Acquired skills: MLOps Fundamentals, Experiment Tracking with MLflow, Model Deployment with FastAPI and Docker, Pipeline Automation with Airflow, Model Monitoring and CI/CD
course
Objects and Prototypes in JavaScript
1 hour 13 chaptersBeginner
Acquired skills: JavaScript Objects, Object Creation and Manipulation, Property Descriptors, Prototype Chain, Prototypal Inheritance, Object Composition
course
Testing JavaScript Code
1 hour 14 chaptersBeginner
Acquired skills: JavaScript Testing Fundamentals, Jest Basics, Writing Unit Tests, Testing Asynchronous Code, Mocking and Spying Functions, Test-Driven Development Mindset
course
Transfer Learning Essentials with Python
1 hour 11 chaptersBeginner
1 STUDYING NOW
Acquired skills: Transfer Learning Fundamentals, Fine-tuning Pre-trained Models, Transfer Learning in CV, Transfer Learning in NLP
course
TypeScript and the DOM
2 hours 18 chaptersBeginner
Acquired skills: TypeScript DOM Typing, Type-Safe Event Handling, Form Validation with Types, TypeScript Generics for DOM, Null Safety in DOM Manipulation
course
Working with Dates and Times in JavaScript
2 hours 14 chaptersIntermediate
Acquired skills: JavaScript Date Basics, Date Component Manipulation, Date Formatting, Date Calculations, Time Zones and UTC Handling, Modern Date Libraries
course
Working with JSON and Local Storage in JavaScript
1 hour 13 chaptersBeginner
Acquired skills: JSON Structure, JSON Parsing and Stringifying, localStorage Usage, sessionStorage Usage, Persistent Data Storage in Browser
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Web Development with C#
7 Courses
292 TasksBeginner
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Python from Zero to Hero
6 Courses215 TasksBeginner
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С++ Essentials
6 Courses117 TasksBeginner
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Java Essentials
7 Courses376 TasksBeginner
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Mastering Data Visualization
5 Courses147 TasksIntermediate
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Machine Learning Mastery
7 Courses182 TasksIntermediate
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4 Courses85 TasksAdvanced
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Java Web
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Access to all content with one subscription
Career opportunitiesLearn about the most popular professions, average salaries, and companies actively seeking specialists in this field.
Data Scientist
Front End Developer
Application Developer
Mobile App Developer
Data Visualization Specialist
$149k
$197k
$246k
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Average
Max
Annual salary
(Average in the US)
Hiring companies
*Source: Glassdoor
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Programming Courses: Key Info and Questions
Introduction to Programming Courses
Introduction to Programming courses provide a foundational understanding of coding concepts and languages, typically starting with beginner-friendly languages like Python or JavaScript. These courses cover basic principles such as variables, loops, and functions, offering hands-on projects and exercises. They are designed to build problem-solving skills and prepare learners for more advanced programming challenges.
Benefits of our Programming Courses
Our programming courses offer the benefits of AI-assisted learning and a progressive UI design, ensuring an engaging and efficient educational experience. With up-to-date content and hands-on projects, learners can master programming concepts effectively. Additionally, our courses provide personalized feedback, fostering a deeper understanding and skill development tailored to individual learning needs.
Career opportunities after completion of Programming Courses
After completing programming courses, you can pursue careers as software developers, web developers, data analysts, system administrators, or tech consultants. These roles are in high demand across various industries, including tech, finance, healthcare, and education. Programming skills can also lead to opportunities in project management, business analysis, and entrepreneurial ventures in the tech space.
Programming Course Options
Codefinity offers various programming courses tailored to different skill levels and interests. Options include beginner courses in Python and JavaScript, advanced courses in data science and machine learning, and specialized tracks in web development and software engineering. Each course features up-to-date content, interactive projects, and expert guidance to help learners achieve their programming goals effectively
Certificate Information
Codefinity offers certificates upon course completion, validating your skills and knowledge in specific areas. These certificates are a valuable addition to your resume, showcasing your commitment to learning and proficiency in the subject. They can enhance your career prospects by providing tangible evidence of your expertise to potential employers
What is programming and why is it important?
Programming involves writing instructions that a computer can execute. It's crucial because it enables the creation of software applications, automation of tasks, and solving complex problems efficiently
Where is Programming Used and Its Significance?
Programming is used in various fields such as web development, artificial intelligence, data analysis, robotics, and more. Also it's used in many industries, including healthcare, finance, and engineering, to streamline processes and improve efficiency. Its significance lies in enabling innovation, enhancing productivity, and facilitating technological advancements
What are the Career Opportunities in Programming?
Career opportunities in programming extend into tech roles like software developer, web designer, and data analyst, as well as non-tech roles such as project manager, tech consultant, and business analyst. These positions benefit from programming skills, offering diverse career paths across industries like finance, healthcare, education, and entertainment
How can Learning Programming Benefit My Career?
Learning programming can enhance problem-solving skills, increase employability in tech-driven industries, and open up opportunities in high-demand, well-paying technology roles
How to Choose the Suitable Programming Course?
Choose a programming course based on your goals: If you aim for web development, look for courses focusing on HTML, CSS, and JavaScript. For data science, prioritize Python and R. Additionally, consider courses with hands-on projects, such as building a website or analyzing real datasets, to ensure practical learning aligned with industry standards
What is the Cost of Training for Programming Courses?
Costs for programming courses range from free online tutorials, to $35-$300 for specialized online courses on platforms like Codefinity. Professional coding bootcamps can cost between $8,000 and $20,000, while university computer science programs may run up to $50,000 per year, depending on the institution
Which Programming Course is Best Suited for Beginners?
For beginners, courses labeled as "Basic", "Beginner" or "Introduction" in Python or JavaScript are ideal due to their straightforward syntax and broad applicability. These courses cover fundamental concepts and provide a gentle introduction to coding, making them perfect for those new to the field without overwhelming them with technical jargon
What are the key skills required to excel in Programming?
To excel in programming, key skills include: logical thinking, proficiency in programming languages, debugging, attention to details, persistence, collaboration, learning agility, communication skills
What impact has programming had on the tech industry in recent years?
Programming has revolutionized the tech industry, driving advancements in AI, cloud computing, cybersecurity, and mobile technologies. It's enabled automation, enhanced data analysis capabilities, and accelerated innovation cycles, transforming how businesses operate and interact with customers globally
What is the best programming course to learn?
The best programming course depends on your goals and interests. For general versatility and ease of learning, "Introduction to Python" is highly recommended due to Python's widespread application in web development, data science, and automation. For those interested in web development, "Introduction to JavaScript" is ideal, offering comprehensive insights into both client and server-side programming
Is coding harder than math?
Coding can be far easier than math for many people. While math often requires understanding abstract theories, coding involves more practical, hands-on problem solving that can be more intuitive. Learning to code through projects and real-world applications can feel more accessible and less daunting than tackling complex mathematical concepts
Are programming courses worth it?
Yes, programming courses are worth it, particularly because they provide a clear learning path, expert instruction, and timely feedback on assignments and projects
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100+ Top-Rated coursesCompletion certificatesAI-Assistant in all courses20+ hands-on Real-world projectsPersonalized study tracksUnlimited workspacesTop courses in the Programming Languages category
1. | Introduction to Python |  4 hours |  46 chapters |
2. | C++ Introduction | 2 hours | 26 chapters |
3. | C# Basics | 6 hours | 63 chapters |
4. | Data Types in Python | 3 hours | 29 chapters |
5. | R Introduction | 4 hours | 44 chapters |
1. Introduction to Python
Hours
Chapters2. C++ Introduction
HoursChapters3. C# Basics
HoursChapters4. Data Types in Python
HoursChapters5. R Introduction
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