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    Python for Data Science

    Python for Data Science Free Course with Certificate

    Learn Python for Data Science for free and become a sought-after data science professional!

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    Python for Data Science

    Prerequisites

    Python for Data Science Course Prerequisites
    • Basic understanding of Programming Concepts
    • Proficiency in Mathematics and Logic
    • Strong Problem-Solving Skills
    Nosql Prerequisites
    • 450,000 +
      Professionals trained
    • 250+
      Workshops every month
    • 100+
      Countries and counting

    Python for Data Science

    Unlocking the Power of Python for Data Science

    20+ Hours of Self-Paced Learning

    Practice with Guided Hands-On Exercises

    Learn-by-Doing with Immersive Learning

    Test Your Learning with Recall Quizzes

    Unlock Knowledge with Interactive eBooks

    Accelerate Progress with Auto-Graded Assessments

    Python has emerged as one of the most popular languages in the data science domain due to its simplicity, versatility, and robust libraries. Python's intuitive and readable syntax, enriched with English keywords, makes it an ideal language for data manipulation and exploration.

    If you're looking for an affordable way to learn Python for data science for free, then this comprehensive free Data Science with Python course is just for you! Whether you're a data enthusiast, data scientist, or a beginner seeking to make a career in data science, this self-paced course offers a seamless journey into the world of Python and its applications in data science, opening doors to exciting career possibilities.

    With our Python for Data Science free course with certificate, dive into Python programming fundamentals with a focus on data analysis and visualization. Gain proficiency in leveraging Python's efficient data structures and libraries through hands-on exercises and practical examples, empowering you to analyze and visualize data effectively.

    Explore the world of machine learning, a powerful subset of data science that enables predictive analysis and pattern recognition, as a part of this course. From natural language processing to speech recognition to computer vision, learn to tackle a wide array of real-world problems with ease leveraging Python's versatility. With simplified explanations and detailed demonstrations, learn building code from scratch, and implement machine learning algorithms with confidence.

    By completing this free Python for data science course with a certificate, you'll gain a strong foundation in Python and be equipped to apply your newfound knowledge confidently. This would validate your newfound expertise in Python and data analysis. This strong foundation will also enable you to navigate the data science landscape with confidence and embark on exciting career opportunities in various industries.

    Gear up to start your journey to learn data science with Python for free and unlock the power of data analysis and machine learning with the language that is transforming the world of data.

    Who Can Attend the Python for Data Science Course

    Who Should Attend
    • Data Scientists
    • Data Analysts
    • Freshers
    • Professionals new to Programming
    • Professionals with Python Experience
    • Students Interested in Learning About Data Science
    Node Js Course

    WHY KNOWLEDGEHUT?

    The KnowledgeHut Edge

    Superior Outcomes

    Focus on skilled-based outcomes with advanced insights from our state-of-the art learning platform.

    Immersive Learning

    Go beyond just videos and learn hands-on with guided exercises, projects, assignments and more.

    Continual Support

    Learn better with support along the way. Get 24/7 help, stay unblocked and ramp up your skills.

    World-Class Instructors

    Course instructors and designers from top businesses including Google, Amazon, Twitter, and IBM.

    Real-World Learning

    Get an intimate, insider look at leading companies in the field through real-world case studies.

    Industry-Vetted Curriculum

    Six months of post-training mentor guidance to overcome challenges in your web development career.

    Build Skills

    Skills You Will Gain
    1
    Fundamentals

    Solid understanding of Python fundamentals

    2
    Data Types

    Ability to handle different data types in Python

    3
    Operators

    Proficiency in using operators in Python.

    4
    Functions

    Knowledge of defining and using functions in Python.

    5
    Indexing & Slicing

    Understanding of indexing and slicing in Python.

    6
    String Handling

    Familiarity with string manipulation techniques in Python.

    NoSQL Curriculum

    1. Introduction to Python

    Learning Objective :

    Get an introduction to working with Python and how to start using it for Data Science.

    Topics

    • Python Introduction
    • Python for Data Science
    • Installation and Setup
    • Hello World

    2. Code and Data

    Learning Objective :

    Learn coding in Python to start managing data through various stages.

    Topics

    • Introduction to Code and Data
    • What is Code and Data?
    • Creating Data
    • Using Data with Code
    • Syntax and Naming Conventions

    3. Building Blocks

    Learning Objective :

    Explore the various components of working with Python including data types, operators, lists, functions, and features.

    Topics

    • Introduction to Building Blocks
    • Data Types
    • Arithmetic Operators
    • Lists Basics
    • Important Functions and Features

    4. Strings

    Learning Objective

    Learn how to work with strings in Python and explore useful concepts and practices.

    Topics

    • Introduction to Strings
    • Creating and Indexing
    • Negative Indexing, Slicing and Stepping
    • Immutability Concept
    • Important String Functions

    Learn Now

    What You Will Learn
    1
    Introduction to Python

    Get started with an overview of Python, a versatile and beginner-friendly programming language.

    2
    Code and Data

    Explore how Python combines code and data, allowing you to manipulate and analyze information effectively.

    3
    Data Types in Python

    Discover the various data types in Python, such as numbers, strings, lists, and dictionaries, enabling you too.

    4
    Operators in Python

    Learn about the operators in Python, including arithmetic, comparison, logic, and assignment operators, enabling you.

    5
    Functions in Python

    Understand the concept of functions in Python, allowing you to create reusable blocks of code for efficient.

    6
    Indexing and Slicing

    Learn how to access specific elements in a string or list using indexes and slices.

    FAQ's

    Frequently Asked Questions

    1. What is Python for data science?

    This free Python for data science course focuses on using Python programming language for data analysis, visualization, and machine learning tasks. Python possesses extensive libraries that can be leveraged for data science. It also allows users to efficiently handle and manipulate large datasets, making it a top choice for data scientists and analysts.

    Python's data science capabilities are enhanced by libraries like NumPy, pandas, Matplotlib, and scikit-learn, which provide powerful tools for various data science tasks. With this, professionals can leverage Python's potential in data science.

    2. Why learn Python for data science?

    Learning Python for data science makes sense as Python is a versatile and widely used programming language. It offers a wide range of libraries and tools used in data manipulation, analysis, and visualization.

    Python's simplicity and readability make it easy to work with large datasets and complex algorithms. Moreover, Python has a strong community and extensive online resources, making support easier to find when needed. A free Data Science with Python course is an excellent way to gain hands-on experience and proficiency.

    3. Is the Data Science with Python program easy to learn?

    This Python for data science free course with certificate is designed to be user-friendly, offering practical examples to help learners better grasp the concepts. This comprehensive course is structured to cater to learners with varying levels of experience, from beginners to those with prior programming knowledge.

    The hands-on nature of the course, along with real-world examples and exercises, enhances the learning experience. This comprehensive approach and self-paced learning ensure that professionals can progress at their own speed.

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