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location Jaipur

Python

Course
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Vidhyawave
IT Institute
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(925 Reviews)
Categories
Development

Our Python Programming Course in Jaipur is designed for beginners, students, graduates, and working professionals who want to build a strong foundation in programming and data analysis. The course starts with Python basics and gradually progresses to intermediate-level concepts, helping you understand how Python is used in software development, automation, web applications, and data science. Through hands-on coding exercises, practical assignments, and real-world projects, you'll gain the confidence to write efficient, clean, and reusable Python code. During the training, you will learn core Python concepts including variables, data types, operators, loops, conditional statements, functions, modules, exception handling, file handling, and Object-Oriented Programming (OOP). The curriculum also covers powerful libraries such as NumPy for numerical computing, Pandas for data manipulation and analysis, Matplotlib for creating professional charts, and Seaborn for advanced statistical data visualization. These tools are widely used by Data Analysts, Data Scientists, Machine Learning Engineers, and Python Developers across industries. By the end of the course, you'll be able to develop Python applications, analyze real-world datasets, automate repetitive tasks, create interactive visualizations, and build practical projects that strengthen your portfolio. Whether your goal is software development, data analytics, machine learning, or AI, this course provides the practical skills and strong programming foundation needed to succeed in today's technology-driven industry.

Key Topics Covered:

Python Fundamentals: Syntax, variables, data types, operators, input/output, loops, conditional statements, functions, modules, exception handling, and file handling.
Object-Oriented Programming (OOP): Classes, objects, inheritance, polymorphism, encapsulation, abstraction, and real-world applications.
NumPy: Arrays, mathematical operations, indexing, slicing, broadcasting, and numerical computing.
Pandas: Series, DataFrames, data cleaning, filtering, grouping, merging, aggregation, and handling missing values.
Matplotlib & Seaborn: Data visualization, line charts, bar charts, histograms, scatter plots, heatmaps, box plots, correlation analysis, and statistical visualization.
Mini Projects: Practical Python programming, data analysis, automation scripts, and real-world project implementation to build industry-ready skills.

Course Content

  • Introduction to Python: History of Python, features, applications, career opportunities, Python installation, and understanding why Python is one of the most popular programming languages.
  • Installing Python: Downloading and installing Python, configuring the PATH variable, verifying installation, and understanding different Python versions.
  • Setting Up the Development Environment: Working with IDLE, Visual Studio Code, Jupyter Notebook, extensions, terminal, virtual environments, and executing Python programs efficiently.
  • Python Syntax & Basic Data Types: Variables, comments, indentation, strings, integers, floats, booleans, type conversion, user input, and output formatting.
  • Operators: Arithmetic, comparison, logical, assignment, membership, identity, and bitwise operators with practical coding examples.
  • Conditional Statements: if, if-else, nested if, elif statements, decision-making logic, and real-world programming scenarios.
  • Lists, Tuples, Dictionaries & Sets: Creating, accessing, updating, slicing, built-in methods, nested collections, and practical data storage techniques.
  • Loops: for loop, while loop, nested loops, break, continue, pass statements, range() function, and iteration over different data structures.
  • Functions: User-defined functions, parameters, return values, default arguments, keyword arguments, lambda functions, recursion, variable scope, and modular programming.

  • Object-Oriented Programming (OOP): Understanding classes, objects, constructors, inheritance, polymorphism, encapsulation, abstraction, method overriding, and building real-world object-oriented applications.
  • NumPy: Introduction to NumPy arrays, array creation, indexing, slicing, reshaping, broadcasting, mathematical operations, statistical functions, and numerical computing with practical examples.
  • Pandas: Working with Series and DataFrames, importing CSV and Excel files, data cleaning, filtering, sorting, grouping, merging, aggregation, handling missing values, and performing Exploratory Data Analysis (EDA).
  • Matplotlib & Seaborn: Creating professional data visualizations including line charts, bar charts, pie charts, histograms, scatter plots, box plots, heatmaps, pair plots, correlation analysis, and customized dashboards for data-driven insights.
  • Mini Projects: Build practical Python projects including data analysis, automation scripts, CSV processing, and visualization dashboards using real-world datasets.
  • Hands-on Assignments: Solve coding exercises, practice problems, quizzes, and real-world case studies to strengthen programming and analytical skills.
  • Career Preparation: Resume building, GitHub portfolio creation, interview preparation, coding challenges, and certification guidance for Python Developer and Data Analyst roles.
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