Python Courses
Choose a course that suits your goals - from the basics to advanced skills in Python.
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Gained skills:
Algorithm DesignApplying RNNs to NLP tasks (sentiment analysis) CRUD OperationsClustering fundamentals and algorithms Code EfficiencyConvolutional Neural NetworksDBSCAN: noise handling and irregular shapes Data Aggregation with pandasData HandlingData Indexing and Selection in pandasData ManipulationData PreprocessingData VisualizationData Visualization TechniquesData normalization and distance metrics Database NormalizationDebuggingDebugging and Exception HandlingDecorator UsageEnd-to-end model development and evaluationError HandlingFile HandlingFile I/O in Python Functional Programming in Python (Python Functions)Gaussian Mixture Models: probabilistic clusteringHandling missing and categorical data Hierarchical clustering and dendrograms Hyperparameter TuningImage Processing with OpenCVImplementing recurrent networks in PyTorchJSON and CSV Data HandlingK-Means: principles and cluster optimization Linear Regression with PythonLogical ThinkingLogistic RegressionMachine Learning with scikit-learnModel Training and EvaluationModule and Package ManagementNeural NetworksNumPy Advanced TechniquesNumPy BasicsNumPy FunctionsObject Detection ApproachesPandas Data ManipulationProblem-SolvingProcessing time series and sequential dataPyTorch BasicsPytestPython BasicsPython ClassesPython Classification ModelsPython CollectionsPython Conditional StatementsPython Data ManipulationPython Data StructuresPython Data TypesPython Function ArgumentsPython FunctionsPython LoopsPython Packing and UnpackingPython ProgrammingPython VariablesPython VisualizationPython Visualization with MatplotlibSQL BasicsSQL in Python ProjectsSeaborn VisualizationStatistics with PythonTensorFlow BasicsUnderstanding RNNs, LSTMs, and GRUsUnittestVariable Scope ManagementWeb Scraping with Python
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Browse Python courses and projects
4 hours
32 chapters
3 hours 27 chapters
3 hours 26 chapters
3 hours 18 chapters
2 hours 13 chapters
3 hours 23 chapters
6 hours 38 chapters
2 hours 19 chapters
3 hours 24 chapters
4 hours 34 chapters
3 hours 22 chapters
2 hours 22 chapters
Level
Type of lesson
Technologies
course
ML Introduction with scikit-learn
4 hours 32 chaptersIntermediate
Acquired skills: Machine Learning with scikit-learn, Model Training and Evaluation, Hyperparameter Tuning
course
Intermediate Python
3 hours 27 chaptersIntermediate
Acquired skills: Python Function Arguments, Variable Scope Management, Decorator Usage, Python Packing and Unpacking, Functional Programming in Python (Python Functions)
course
Ultimate Visualization with Python
3 hours 26 chaptersIntermediate
Acquired skills: Data Visualization, Data Visualization Techniques, Python Visualization, Python Visualization with Matplotlib, Seaborn Visualization
course
Introduction to TensorFlow
3 hours 18 chaptersAdvanced
Acquired skills: TensorFlow Basics, Neural Networks, Python Data Structures, Data Preprocessing
course
Optimization Techniques in Python
2 hours 13 chaptersAdvanced
Acquired skills: Code Efficiency, Python Programming, Python Data Manipulation, Python Functions, Python Conditional Statements
course
Web Scraping with Python
3 hours 23 chaptersIntermediate
Acquired skills: Python Programming, Web Scraping with Python
course
Learning Statistics with Python
6 hours 38 chaptersAdvanced
Acquired skills: Statistics with Python
course
Linear Regression with Python
2 hours 19 chaptersIntermediate
Acquired skills: Linear Regression with Python, Model Training and Evaluation
course
Classification with Python
3 hours 24 chaptersIntermediate
Acquired skills: Python Programming, Python Classification Models, Logistic Regression, Data Preprocessing, Model Training and Evaluation, Hyperparameter Tuning
course
Cluster Analysis
4 hours 34 chaptersIntermediate
Acquired skills: Clustering fundamentals and algorithms , Handling missing and categorical data , Data normalization and distance metrics , K-Means: principles and cluster optimization , Hierarchical clustering and dendrograms , DBSCAN: noise handling and irregular shapes , Gaussian Mixture Models: probabilistic clustering
course
Introduction to RNNs
3 hours 22 chaptersIntermediate
Acquired skills: Understanding RNNs, LSTMs, and GRUs, Implementing recurrent networks in PyTorch, Processing time series and sequential data, Applying RNNs to NLP tasks (sentiment analysis) , End-to-end model development and evaluation
shorts
Casual Introduction to Python
2 hours 22 chaptersBeginner
Acquired skills: Python Basics, Python Conditional Statements, Python Data Types, Python Loops
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Career opportunitiesLearn about the most popular professions, average salaries, and companies actively seeking specialists in this field.
Data Scientist
Data Engineer
Machine Learning Engineer
AI Researcher
Python Developer
$149k
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Chosen by students of top schools
Including 30 out of top-30 U.S. colleges
Python Courses: Key Info and Questions
What is covered in Python Courses?
Python courses provide a foundational understanding of Python programming, covering basics like syntax, variables, data types, and control structures. These courses often include hands-on projects and real-world examples, making learning engaging and practical. Ideal for beginners, they help build essential skills needed for various applications in data analysis, web development, automation, and more
What are the benefits of your Python Courses?
Our Python courses offer comprehensive learning paths with AI assistance, catering to all skill levels from beginner to advanced. These courses cover various specializations, ensuring you gain practical skills applicable to your career goals. The interactive content and personalized feedback help you master Python efficiently, regardless of your starting point or destination.
What career opportunities are available after completing Python Courses?
Completing a Python course can open various career opportunities, including roles as a software developer, data analyst, machine learning engineer, web developer, and automation tester. Python skills are highly sought after across industries such as technology, finance, healthcare, and education, offering competitive salaries and numerous job prospects for those proficient in the language.
What Python Course Options are available?
Python course options range from beginner to advanced levels, including "Python for Beginners" for foundational skills, "Data Analysis with Python" for those interested in data science, and "Python for Web Development" for aspiring web developers. Courses typically offer a mix of video tutorials, interactive exercises, and real-world projects to enhance learning and practical application.
Can you provide information about Python course certificates?
Upon successfully completing a Python course, you will receive a certificate that verifies your skills and knowledge. This can be a valuable asset when applying for jobs or demonstrating your proficiency to employers. Our certificates are recognized in the industry and can help you stand out in a competitive job market.
What is Python and why is it important?
Python is a versatile, high-level programming language known for its readability and straightforward syntax. It's important because it supports multiple programming paradigms and is widely used in web development, data analysis, artificial intelligence, scientific computing, and automation. Its extensive libraries and frameworks make it a preferred choice for both beginners and professionals in diverse industries.
How do I choose the right Python Course?
To choose the right Python course, identify your learning goals—whether it's data science, web development, or general programming. Look for courses that match your learning style, whether video tutorials, interactive coding sessions, or text-based materials. Consider beginner-friendly courses with practical projects, such as "Django: Build Your First Website" to apply your learning effectively.
Which course is best in the category of Python Courses?
In the category of Python courses, "Analyzing and Visualizing Real-World Data" stands out as exceptionally practical and beginner-friendly. It teaches Python basics through real-world applications like automating tasks and parsing information, making it ideal for those looking to immediately apply their skills to everyday problems, thereby enhancing both learning and productivity.
Why should I consider taking an online Python course with your company?
Taking an online Python course with our company offers expertly crafted curriculum, real-time support from experienced instructors, AI assistance, and interactive projects that mirror real-world scenarios. Whether you're a beginner or advancing your skills, our courses are designed to help you succeed at your own pace.
What tips do you have for successful Python course completion?
To successfully complete a Python course, stay consistent with practice and apply concepts through small projects. Regularly test your understanding with quizzes and exercises. Lastly, don't rush; take time to thoroughly understand each concept before moving on, as a strong foundation is crucial for advanced topics.
Which Python Course is best suited for beginners?
For beginners, "Introduction to Python" is an excellent choice. It covers Python basics and gradually moves into more complex topics such as functions, making it ideal for those with no prior programming experience. The course includes hands-on tasks to apply what you've learned effectively.
What are the key skills required to excel in Python?
To excel in Python, key skills include proficiency in Python syntax, problem-solving abilities, mastery of popular libraries like NumPy and Pandas, familiarity with frameworks like Django, and debugging skills. Additionally, using tools like Git for managing code changes is essential.
How does Python compare to other programming languages like Java or C++?
Python is known for its simplicity and readability, making it ideal for beginners. It has a gentler learning curve compared to Java or C++, which involve more complex syntax and static typing. Python's versatility allows for applications in web development, data analysis, and AI, whereas Java and C++ are preferred for enterprise solutions and performance-intensive applications, respectively.
What impact has Python had on the industry in recent years?
Python has had a profound impact on the industry by simplifying complex processes in data analysis, machine learning, and web development. Its easy-to-learn syntax and vast libraries have democratized programming, enabling a wider range of professionals to automate tasks, analyze data, and build applications efficiently, driving innovation and operational efficiencies across multiple sectors.
Is 3 months enough to learn Python?
Yes, three months is sufficient to learn Python fundamentals if you dedicate consistent effort. This period allows you to grasp basic syntax, control structures, functions, and data types. With daily practice and projects, you can develop a solid foundation and even explore more advanced topics like web development with Django or data analysis with libraries like Pandas.
How long does it realistically take to learn Python?
With dedicated daily practice and smart guidance, it is realistic to become proficient in Python within about 6 months. This timeline can vary based on prior programming experience and the complexity of the projects undertaken, but consistent effort and quality instruction will enable a solid understanding of both fundamental and more advanced Python concepts within this timeframe.
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100+ Top-Rated coursesCompletion certificatesAI-Assistant in all courses20+ hands-on Real-world projectsPersonalized study tracksUnlimited workspacesTop courses in the Python category
1. | Introduction to Python |  4 hours |  46 chapters |
2. | Introduction to Python with AI | 2 hours | 20 chapters |
3. | Data Types in Python | 3 hours | 33 chapters |
4. | Conditional Statements in Python | 1 hours | 15 chapters |
5. | Python Data Structures | 3 hours | 31 chapters |
1. Introduction to Python
Hours
Chapters2. Introduction to Python with AI
HoursChapters3. Data Types in Python
HoursChapters4. Conditional Statements in Python
HoursChapters5. Python Data Structures
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