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Data Analytics with Python - Hindi
Highest Rated
Rating: 4.8 out of 5(50 ratings)
324 students

Data Analytics with Python - Hindi

Essential Skills for Aspiring Data Analysts
Highest Rated
Created bySelfcode Academy
Last updated 11/2024
Hindi

What you'll learn

  • Python Fundamentals: Learn Python basics, including syntax, data types, and functions for efficient data analysis coding.
  • Data Manipulation and Analysis: Gain proficiency in NumPy and pandas for manipulating and analyzing data of any size or complexity.
  • Exploratory Data Analysis (EDA): Explore datasets, identify patterns, and visualize insights for informed decision-making.
  • Applied Data Analytics Skills: Develop hands-on skills in data cleaning, preprocessing, and analysis through practical projects.

Course content

11 sections • 44 lectures • 16h 55m total length

  • Introduction to Business and Data22:54

Requirements

  • Basic Computer Literacy: Familiarity with using a computer and navigating the operating system.
  • No Prior Programming Experience Needed: The course starts from scratch, making it suitable for beginners.
  • Access to a Computer: Learners should have access to a computer or laptop with internet connectivity.
  • Python Installation: Prior to the course, students should have Python installed on their computer (instructions will be provided).
  • Eagerness to Learn: An open mind and willingness to dive into the world of data analytics with Python.

Description


Mastering Data Analysis with Python: From Fundamentals to Advanced Techniques


Are you ready to dive deep into the realm of data analysis and unlock the potential of Python as your go-to tool? Our comprehensive course offers a holistic learning experience tailored to equip you with the skills and knowledge essential for success in the dynamic field of data analytics.


Beginning with an exploration of the fundamental principles of business and data, you'll gradually immerse yourself in the world of Python programming through interactive sessions and hands-on exercises. From mastering Python basics and syntax to understanding advanced concepts such as object-oriented programming and NumPy, each module is meticulously crafted to build a strong foundation and enhance your analytical capabilities.


As you progress through the course, you'll unravel the power of data manipulation and analysis using industry-standard libraries like pandas, gaining practical insights into handling real-world datasets with ease. Through guided projects and lab sessions, you'll have the opportunity to apply your newfound skills to solve complex data challenges and derive actionable insights.


Whether you're a seasoned professional looking to upskill or a newcomer eager to explore the world of data, this course is designed to cater to learners of all backgrounds and levels of expertise. Join us on this exciting journey and unleash the full potential of data analysis with Python!


Major Topics Covered:

  1. Introduction to Business and Data: Understanding the role of data in driving business decisions.

  2. Python Basics and Jupyter Notebooks: Exploring the fundamentals of Python programming and interactive computing.

  3. Basic Python Syntax and Conditional Programming: Mastering syntax fundamentals and conditional logic.

  4. Functions and Sequences: Understanding the principles of functions and sequences in Python.

  5. Object-Oriented Programming (OOP) and NumPy: Delving into object-oriented programming concepts and leveraging NumPy for numerical computing.

  6. pandas Library and Data Manipulation: Exploring data manipulation techniques using the pandas library.

  7. Working with Files and Data Importing: Managing files and importing data from various sources.

  8. Data Cleaning and Preprocessing: Learning techniques for cleaning and preprocessing raw data for analysis.

  9. Exploratory Data Analysis (EDA): Conducting exploratory data analysis to gain insights and identify patterns.

  10. Advanced Topics: Data Gathering, Linear Algebra, and APIs: Exploring advanced topics such as data gathering techniques, linear algebra operations, and working with APIs.

  11. Capstone Project: Applying acquired skills to a real-world data analysis project, from data cleaning to visualization and interpretation.



Enroll now and embark on your journey to mastering data analysis with Python!


Who this course is for:

  • Students and Graduates: University students or recent graduates seeking practical skills in data analytics.
  • Career Changers: Professionals from diverse backgrounds aiming to transition into the field of data analysis.
  • Self-Learners: Anyone with a passion for data and a desire to learn Python for data analysis purposes.
  • Professionals Seeking Skill Enhancement: Those already working in data-related roles who wish to enhance their Python and data analysis skills.
  • Aspiring Data Analysts: Individuals looking to kickstart or advance their career in data analysis.

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