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:

1. 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.   

2. 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.   

3. 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. 

4. 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:

A solid foundation in Python programming for data science

Practical experience through mini-projects that reinforce your learning

The ability to tackle real-world data science and data analysis challenges

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:

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

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

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:

1. Python Fundamentals: You’ll master the basics of Python programming, including syntax, data structures, and control flow

2. Data Science Essentials: You’ll delve into key data science concepts, tools, and libraries

3. Hands-On Experience: You’ll gain practical experience through a series of mini-projects and exercises that reinforce your learning

4. Real-World Applications: You’ll understand how Python is used to solve real-world data science and data analysis challenges

Why This Course?

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

Incremental Progress: Our step-by-step approach ensures that you build your skills progressively, with each tutorial video building upon the previous one

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

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

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:

1. Python programming

2. Data analysis

3. Data science

4. Numpy

5. Pandas

6. Matplotlib

7. Seaborn

8. Bokeh

9. Scikit-Learn

10. Data visualization

11. Data manipulation

12. Machine learning

13. Python essentials

14. Data preprocessing

15. Data cleaning

16. Data visualization libraries

17. Data analysis tools

18. Data wrangling

19. Data exploration

20. 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

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!