Add to Wishlist

Python Programming

Enroll course

    Welcome to Technofine24’s Python Programming Training! As the best training institute for Python, we provide a comprehensive program designed for both beginners and experienced developers. Our training ensures you master Python, one of the most versatile and in-demand programming languages.

    KEY FEATURES

    • Comprehensive Curriculum
    • Expert Instructors
    • Interactive Learning
    • Flexible Options
    • Support and Resources
    • Certification

    Course Objectives

    The Python course by Technofine24 aims to equip learners with comprehensive skills in Python programming. Key objectives include:

    • Foundational Knowledge: Understand Python syntax, data types, and control structures.
    • Advanced Concepts: Master functions, modules, file handling, and error handling.
    • Data Handling: Gain proficiency in working with libraries like NumPy, Pandas, and Matplotlib for data analysis and visualization.
    • Web Development: Learn the basics of web frameworks like Django and Flask.
    • Project Development: Apply concepts through hands-on projects and real-world scenarios.
    • Problem Solving: Enhance problem-solving abilities using Python.
    • Career Readiness: Prepare for Python-related job roles with practical coding exercises and interview preparation.

    This course is designed for both beginners and those looking to advance their Python skills.

    Salary Expectations for a Fresher

    Completing the Python course training by Technofine24 positions freshers for promising career opportunities in the tech industry. Entry-level Python developers can expect starting salaries ranging from $60,000 to $80,000 per year, depending on location, company size, and industry. High-demand sectors like finance, healthcare, and tech startups often offer competitive packages. Additionally, roles such as data analyst, web developer, and software engineer typically provide strong growth potential and benefits. Mastery of Python through Technofine24’s comprehensive training can significantly enhance employability and salary prospects for fresh graduates entering the job market.

    Why Python?

    • Versatile and Powerful: Used in web development, data science, AI, and automation.
    • Simple and Readable: Ideal for both beginners and experienced developers.
    • Extensive Libraries and Frameworks: Includes Django, Flask, NumPy, and Pandas for increased productivity.
    • Strong Community Support: Access to a wealth of resources and assistance.
    • Cross-Platform Compatibility: Works seamlessly across different operating systems.
    • High Demand: Skills are sought after across various industries, offering numerous career opportunities.
    • Technofine24’s Comprehensive Training: Provides the expertise needed to excel in this dynamic field.

    Roles and Responsibilities of Python Developer

    A Python developer plays a crucial role in various industries. Key responsibilities include:

    • Developing and Maintaining Code: Write clean, efficient, and reusable Python code for applications.
    • Web Development: Build server-side logic, integrate front-end elements, and work with frameworks like Django and Flask.
    • Data Handling: Analyze and visualize data using libraries like Pandas and Matplotlib.
    • Automation: Create scripts to automate repetitive tasks.
    • Testing and Debugging: Perform code reviews, write unit tests, and troubleshoot issues.
    • Collaboration: Work with cross-functional teams including designers, developers, and stakeholders.
    • Continuous Learning: Stay updated with the latest Python trends and technologies.

    Technofine24’s training prepares you to excel in these roles with practical skills and industry knowledge.

    COURSE CONTENT

    1. Introduction To Python

    1. Installation and Working with Python
    2. Understanding Python variables
    3. Python basic Operators
    4. Understanding the Python blocks.

    3. Introduction To Variables

    1. Variables, expression condition and function
    2. Global and Local Variables in Python
    3. Packing and Unpacking Arguments
    4. Type Casting in Python
    5. Byte objects vs. string in Python
    6. Variable Scope

    5. Control Structure & Flow

    1. Statements – if, else, elif
    2. How to use nested IF and Else in Python
    3. Loops
    4. Loops and Control Statements.
    5. Jumping Statements – Break, Continue, pass
    6. How to use Range function in Loop?
    7. Programs for printing Patterns in Python
    8. How to use if and else with Loop
    9. Use of Switch Function in Loop
    10. How to use nested Loop in Python
    11. Use If and Else in for and While Loop
    12. Examples of Looping with Break and Continue Statement

    7. List

    1. What is a List?
    2. Advantage of using a list.
    3. Creation of a list.
    4. Different operations on a list using inbuilt functions.
    5. Operations on a list using user-defined functions.
    6. Indexing and Slicing in list.
    7. Implementation of list data structure in the form of a micro-project.
    8. Using List Comprehension.

    9. Dictionary

    1. What is a Dictionary?
    2. Advantage of using a Dictionary.
    3. Creation of a Dictionary.
    4. Different operations on a Dictionary using inbuilt functions.
    5. Operations on a Dictionary using user-defined functions.
    6. Implementation of Dictionary data structure in the form of a mini-project.
    7. Ordered Dictionary

    11. Strings

    1. What is a String?
    2. Advantage of using a String.
    3. Creation of a String.
    4. Different operations on a String using inbuilt functions.
    5. Operations on a String using user-defined functions.
    6. Implementation of String data structure in the form of a micro-project.

    13. File Handling

    1. What is File Handling?
    2. Different modes in file handling.
    3. Opening a file in different modes.
    4. Reading, Writing and Appending to a file.
    5. Configuring the current working directory for files.
    6. List Directories and Files.
    7. Making new directory.
    8. Changing the file directory.

    15. Data Analysis - NUMPY

    1. Introduction to Numpy – Numerical Python
    2. Importing Numpy
    3. Introduction to Arrays
    4. Operations on an array using Numpy
    5. Two Dimensional Arrays
    6. Operations on 1-D and 2-D Arrays
    7. Logical Operations with Arrays

    17. Data Analysis - MATPLOTLIB

    1. Introduction to Matplotlib.
    2. Importing Matplotlib.
    3. Working on different types of charts using matplotlib.
    4. Exporting the chart as an image.
    5. Customization of the charts using matplotlib.
    6. Implementing pandas and matplotlib to create interactive visualizations.

    19. Statistics using Python

    1. Introduction to Descriptive statistics.
    2. Importing Inferential statistics.
    3. Understanding the data using mean, median ,mode, standard deviation.
    4. Using python’s statistics module to understand the data.

    21. EDA - PROJECTS

    1. EDA – Projects
      1. Covid Data
      2. IPL Data
      3. Analysis of Olympics dataset

    2. Python Keywords and Identifiers

    1. Python Keyword and Identifiers
    2. Python Comments, Multiline Comments.
    3. Python Indentation
    4. Understating the concepts of Operators
      1. Arithmetic
      2. Relational
      3. Logical
      4. Assignment
      5. Membership
      6. Identity

    4. Data Types

    1. Declaring and using Numeric data types
    2. Using string data type and string operations
    3. Understanding Non-numeric data types
    4. Understanding the concept of Casting and Boolean.
    5. Strings
    6. List
    7. Tuples
    8. Dictionary
    9. Sets

    6. Functions, Modules and Packages

    1. What is a Function?
    2. Function Call and Return Statement
    3. Arguments in a function : Required, Default, Positional and Variable-length
    4. Lambda Functions
    5. Scope and lifetime of a variable in python
    6. Recursion and recursive functions
    7. Organizing python codes into functions and modules
    8. Importing the modules
    9. Random Functions
    10. Map, Filter and Reduce Functions

    8. Tuple

    1. What is a Tuple?
    2. Advantage of using a Tuple.
    3. Creation of a Tuple.
    4. Different operations on a Tuple using inbuilt functions.
    5. Operations on a Tuple using user-defined functions.
    6. Indexing and Slicing in Tuple.
    7. Implementation of Tuple data structure in the form of a micro-project.

    10. Sets

    1. What is a Set?
    2. Advantage of using a Set.
    3. Creation of a Set.
    4. Different operations on a Set using inbuilt functions.
    5. Operations on a Set using user-defined functions.
    6. Implementation of Set data structure in the form of a micro-project.
    7. Frozen Sets.

    12. Exceptional Handling

    1. What is Exceptional Handling?
    2. Error, Bug and Exception.
    3. Python Errors and built-in exceptions.
    4. Try, Except and Finally.
    5. Catching exceptions in Python.
    6. Raising Exceptions.
    7. Using else with Python Try and Except Block.

    14. Database Handling

    1. What is a database?
    2. Introduction to mysql database and its queries using xampp.
    3. Establishing the connection using mysql-connector.
    4. Inserting the data in database using python.
    5. Reading and fetching the data from database.
    6. Updating the data in the database tables using python.

    16. Data Analysis - PANDAS

    1. Introduction to Pandas.
    2. Importing Pandas.
    3. Working with excel and csv files using pandas.
    4. Working with dataframes and series.
    5. Data cleaning and data preprocessing using pandas.
    6. Writing to excel or csv files using pandas.
    7. Getting the data from web urls.

    18. Data Analysis - SEABORN

    1. Introduction to Seaborn.
    2. Importing Seaborn.
    3. Working on different types of charts using Seaborn.
    4. Exporting the chart as an image.
    5. Customization of the charts using seaborn.
    6. Implementing pandas and Seaborn to create interactive visualizations.
    7. Working on advanced functions of seaborn.

    20. EDA - Exploratory Data Analysis

    1. Introduction to EDA.
    2. Data Pre-Processing steps.
    3. Working on different types of unstructured data using python to explore them.
    No announcements at this moment.

    Be the first to add a review.

    ×