Python for Data Science and Data Analysis
Python for Data Science and Data Analysis, available at $64.99, has an average rating of 3.7, with 156 lectures, based on 189 reviews, and has 827 subscribers.
You will learn about Learn how to start with Python 3 Gain confidence in usual problem-solving techniques that you will encounter on a day to day basis as a programmer In-depth study of Variables and Operators in Python In-depth study of Functions and Modules in Python In-depth study of data structures (Lists, Tuples, Sets, and Dictionaries) Learn to use NumPy for Numerical Data Processing Learn to use Matplotlib, Seaborn and Bokeh for Data Visualization Learn to use Pandas for Data Manipulation and Data Analysis Learn to use SciKit-Learn for Machine Learning Tasks Learn to use Python for Data Science and Machine Learning Apply the concepts and models you learn in this course in the real world using COVID19 data This course is ideal for individuals who are This course is for you if you want to master writing code in Python for Data Science and Machine Learning or This course is for you if you are looking for a simple and inexpensive Python course. or This course is for you if you like doing as you learn or This course is for you if you want to shorten your learning curve in programming. or You’ll simply love this course as there’s plenty of excitement in the form of challenging homework. It is particularly useful for This course is for you if you want to master writing code in Python for Data Science and Machine Learning or This course is for you if you are looking for a simple and inexpensive Python course. or This course is for you if you like doing as you learn or This course is for you if you want to shorten your learning curve in programming. or You’ll simply love this course as there’s plenty of excitement in the form of challenging homework.
Enroll now: Python for Data Science and Data Analysis
Summary
Title: Python for Data Science and Data Analysis
Price: $64.99
Average Rating: 3.7
Number of Lectures: 156
Number of Published Lectures: 156
Number of Curriculum Items: 156
Number of Published Curriculum Objects: 156
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn how to start with Python 3
- Gain confidence in usual problem-solving techniques that you will encounter on a day to day basis as a programmer
- In-depth study of Variables and Operators in Python
- In-depth study of Functions and Modules in Python
- In-depth study of data structures (Lists, Tuples, Sets, and Dictionaries)
- Learn to use NumPy for Numerical Data Processing
- Learn to use Matplotlib, Seaborn and Bokeh for Data Visualization
- Learn to use Pandas for Data Manipulation and Data Analysis
- Learn to use SciKit-Learn for Machine Learning Tasks
- Learn to use Python for Data Science and Machine Learning
- Apply the concepts and models you learn in this course in the real world using COVID19 data
Who Should Attend
- This course is for you if you want to master writing code in Python for Data Science and Machine Learning
- This course is for you if you are looking for a simple and inexpensive Python course.
- This course is for you if you like doing as you learn
- This course is for you if you want to shorten your learning curve in programming.
- You’ll simply love this course as there’s plenty of excitement in the form of challenging homework.
Target Audiences
- This course is for you if you want to master writing code in Python for Data Science and Machine Learning
- This course is for you if you are looking for a simple and inexpensive Python course.
- This course is for you if you like doing as you learn
- This course is for you if you want to shorten your learning curve in programming.
- You’ll simply love this course as there’s plenty of excitement in the form of challenging homework.
Welcome to the comprehensive and hands-on course, “Mastering Python for Data Science & Data Analysis.” Whether you’re a beginner or have some prior Python knowledge, this course is designed to help you harness the power of Python for solving real-world data science and data analysis problems.
Python is a versatile programming language widely used in the field of data science due to its simplicity and robust libraries. In this course, we will guide you through the essentials of Python for data science, regardless of your programming or statistical background. While prior experience is not required, the course is structured to provide practical learning experiences to solidify your understanding.
Here’s what you can expect from this course:
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Hands-On Learning: We believe that the best way to learn Python is by doing. That’s why you’ll find a series of mini-projects throughout this course. These projects will give you practical experience and help you apply your Python skills to real-world scenarios.
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Building a Strong Foundation: You’ll start by mastering the fundamentals of Python programming. We will guide you through Python syntax, data structures, and essential libraries commonly used in data science and data analysis.
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Step-by-Step Progress: This course is structured to take you on a journey of incremental learning. Each tutorial video builds upon what you’ve already learned, ensuring that you grasp new concepts before moving forward. After each theoretical explanation, you’ll immediately apply your knowledge by solving small tasks.
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Code-Along and Exercises: You’ll have the opportunity to code along with the instructor and complete well-planned exercises. This hands-on approach will boost your confidence in using Python for data science tasks.
By the end of this course, you will have:
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A solid foundation in Python programming for data science
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Practical experience through mini-projects that reinforce your learning
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The ability to tackle real-world data science and data analysis challenges
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Confidence in Python syntax and libraries commonly used in data science
Whether you’re looking to kickstart a career in data science, enhance your Python skills, or simply gain practical knowledge in data analysis, this course is designed to meet your needs. Novices in Python and data science will find it informative and practical, while those with some experience will benefit from the hands-on projects that deepen their understanding.
Don’t miss this opportunity to become a proficient Python developer and data scientist. Enroll in this course and embark on your journey to mastering Python for data science and data analysis.
Who Should Take This Course?
This course is suitable for:
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Beginners: If you have no prior experience in Python or data science, this course provides a perfect starting point. You’ll learn Python from scratch and gradually delve into data science and analysis
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Python Enthusiasts: If you already have some Python knowledge and want to apply it to data science and analysis, this course will help you bridge the gap and develop practical skills
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Aspiring Data Scientists: If you aspire to become a data scientist, this course lays a strong foundation by teaching you Python and essential data science concepts
What You Should Learn:
By enrolling in this course, you can expect to learn:
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Python Fundamentals: You’ll master the basics of Python programming, including syntax, data structures, and control flow
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Data Science Essentials: You’ll delve into key data science concepts, tools, and libraries
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Hands-On Experience: You’ll gain practical experience through a series of mini-projects and exercises that reinforce your learning
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Real-World Applications: You’ll understand how Python is used to solve real-world data science and data analysis challenges
Why This Course?
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Practical Learning: This course emphasizes hands-on learning, ensuring that you not only understand the theory but also apply it through coding exercises and projects
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Incremental Progress: Our step-by-step approach ensures that you build your skills progressively, with each tutorial video building upon the previous one
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Versatile Skills: Python is a versatile language used extensively in data science. By mastering Python, you open doors to a wide range of data-related roles and opportunities
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Strong Foundation: Whether you’re looking to start a career in data science or enhance your Python skills for data analysis, this course provides a solid foundation
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Career Growth: Proficiency in Python for data science is a valuable skill in today’s job market. This course equips you with the knowledge needed for data-related roles
Enroll Today and Start Your Data Science Journey
Don’t miss this opportunity to become a proficient Python developer and data scientist. Enroll in this course and embark on your journey to mastering Python for data science and data analysis. Whether you’re new to the field or seeking to advance your skills, this course will equip you with the knowledge and practical experience needed to excel in data science and data analysis.
List of Keywords:
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Python programming
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Data analysis
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Data science
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Numpy
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Pandas
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Matplotlib
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Seaborn
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Bokeh
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Scikit-Learn
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Data visualization
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Data manipulation
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Machine learning
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Python essentials
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Data preprocessing
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Data cleaning
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Data visualization libraries
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Data analysis tools
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Data wrangling
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Data exploration
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Data science fundamentals
Course Curriculum
Chapter 1: Introduction to the Course
Lecture 1: About the Tutor and AI Sciences
Lecture 2: Introduction To Instructor
Lecture 3: Focus of the Course-Part 1
Lecture 4: Focus of the Course- Part 2
Lecture 5: Feedbacks and Review
Lecture 6: Link to the Python codes for the projects and the data
Chapter 2: Basics of Programming
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: Understanding the Algorithm
Lecture 3: FlowCharts and Pseudocodes
Lecture 4: Example of Algorithms- Making Tea Problem
Lecture 5: Example of Algorithms-Searching Minimun
Lecture 6: Example of Algorithms-Sorting Problem
Lecture 7: Example of Algorithms-Searching Minimun Quiz
Lecture 8: Example of Algorithms-Searching Minimun Solution
Lecture 9: Sorting Problem in Python
Chapter 3: Why Python and Jupyter Notebook
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: Why Python
Lecture 3: Why Jupyter Notebooks
Chapter 4: Installation of Anaconda and IPython Shell
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: Installing Python and Jupyter Anaconda
Lecture 3: Your First Python Code- Hello World
Lecture 4: Coding in IPython Shell
Chapter 5: Variable and Operator
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: Variables
Lecture 3: Operators
Lecture 4: Variable Name Quiz
Lecture 5: Bool Data Type in Python
Lecture 6: Comparison in Python
Lecture 7: Combining Comparisons in Python
Lecture 8: Combining Comparisons Quiz
Chapter 6: Python Useful function
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: Python Function- Round
Lecture 3: Python Function- Round Quiz
Lecture 4: Python Function- Round Solution
Lecture 5: Python Function- Divmod
Lecture 6: Python Function- Is instance and PowFunctions
Lecture 7: Python Function- Input
Chapter 7: Control Flow in Python
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: If Python Condition
Lecture 3: if Elif Else Python Conditions
Lecture 4: if Elif Else Python Conditions Quiz
Lecture 5: if Elif Else Python Conditions Solution
Lecture 6: More on if Elif Else Python Conditions
Lecture 7: More on if Elif Else Python Conditions Quiz
Lecture 8: More on if Elif Else Python Conditions Solution
Lecture 9: Indentations
Lecture 10: Indentations Quiz
Lecture 11: Indentations Solution
Lecture 12: Comments and Problem Solving Practice With If
Lecture 13: While Loop
Lecture 14: While Loop break Continue
Lecture 15: While Loop break Continue Quiz
Lecture 16: While Loop break Continue Solution
Lecture 17: For Loop
Lecture 18: For Loop Quiz
Lecture 19: For Loop Solution
Lecture 20: Else In For Loop
Lecture 21: Loops Practice-Sorting Problem
Chapter 8: Function and Module in Python
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: Functions in Python
Lecture 3: DocString
Lecture 4: Input Arguments
Lecture 5: Multiple Input Arguments
Lecture 6: Multiple Input Arguments Quiz
Lecture 7: Multiple Input Arguments Solution
Lecture 8: Ordering Multiple Input Arguments
Lecture 9: Output Arguments and Return Statement
Lecture 10: Function Practice-Output Arguments and Return Statement
Lecture 11: Variable Number of Input Arguments
Lecture 12: Variable Number of Input Arguments Quiz
Lecture 13: Variable Number of Input Arguments Solution
Lecture 14: Variable Number of Input Arguments as Dictionary
Lecture 15: Variable Number of Input Arguments as Dictionary Quiz
Lecture 16: Variable Number of Input Arguments as Dictionary Solution
Lecture 17: Default Values in Python
Lecture 18: Modules in Python
Lecture 19: Making Modules in Python
Lecture 20: Function Practice-Sorting List in Python
Chapter 9: String in Python
Lecture 1: Link to the Python codes for the projects and the data
Lecture 2: Strings
Lecture 3: Multi Line Strings
Lecture 4: Indexing Strings
Lecture 5: Indexing Strings Quiz
Lecture 6: Indexing Strings Solution
Lecture 7: String Methods
Lecture 8: String Methods Quiz
Lecture 9: String Methods Solution
Lecture 10: String Escape Sequences
Lecture 11: String Escape Sequences Quiz
Lecture 12: String Escape Sequences Solution
Chapter 10: Data Structure (List, Tuple, Set, Dictionary)
Instructors
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AI Sciences
AI Experts & Data Scientists |4+ Rated | 168+ Countries -
AI Sciences Team
Support Team AI Sciences
Rating Distribution
- 1 stars: 5 votes
- 2 stars: 7 votes
- 3 stars: 30 votes
- 4 stars: 64 votes
- 5 stars: 83 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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