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Avishek Majumder
Begin your data science adventure with our introductory course, focusing on Python programming essentials. Master Python setup, syntax, and control structures. Dive into data structures like lists and tuples, and enhance your skills with essential algorithms and Python libraries. Perfect for beginners aiming to build a strong foundation in Python for data science.
Register for this course and see more details by visiting:
OpenCourser.com/course/oatxw9/python
What's inside
Learning objectives
- Grasp python programming basics and set up your python environment.
- Understand and implement essential data structures like lists, tuples, and dictionaries.
- Develop algorithmic thinking for problem-solving.
- Learn basic algorithms for sorting and searching, and get introduced to complexity analysis.
- Grasp python programming basics and set up your python environment.
- Understand and implement essential data structures like lists, tuples, and dictionaries.
- Develop algorithmic thinking for problem-solving.
- Learn basic algorithms for sorting and searching, and get introduced to complexity analysis.
Syllabus
Unit 1.1.1 Python Basics and Environment Setup
Introduction to Python Programming
Setting up Python Environment
Basic Syntax and Control Structures
Read more
Syllabus
Unit 1.1.1 Python Basics and Environment Setup
Introduction to Python Programming
Setting up Python Environment
Basic Syntax and Control Structures
Read more
Functions and Modules
Working with Python Libraries
Understanding Basic Data Structures: Lists, Tuples, Sets, Dictionaries
Algorithmic Thinking and Problem Solving
Basic Algorithms: Sorting and Searching
Introduction to Complexity Analysis
Unit2. 1.2 Introduction to Data Structures and Algorithms
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops Python programming essentials, data structures, and algorithmic thinking, which are core skills for data science
Taught by Avishek Majumder, who is recognized for his work in data science and Python programming
Emphasizes practical skills through hands-on labs and interactive materials
Builds a strong foundation for beginners, providing a comprehensive introduction to Python for data science
Requires students to come in with no prior programming experience
Focuses on essential Python libraries for data science, such as NumPy and Pandas
Save this course
Save Python Power Up: Coding Foundations for Data Wizards to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Python Power Up: Coding Foundations for Data Wizards with these
activities:
Organize Course Materials
Show steps
Establish a structured approach by organizing notes, assignments, quizzes, and exams for easy reference and review.
Show steps
-
Create folders or use a note-taking app to categorize materials.
-
Review materials regularly to reinforce your understanding.
Revisit Python Syntax
Show steps
Ensure familiarity with Python's syntax by reviewing the core syntax elements, such as keywords, operators, and indentation.
Browse courses on
Python Syntax
Show steps
-
Go through the course materials or online tutorials that cover Python syntax.
-
Practice writing simple Python code snippets to refresh your memory.
Review Basic Programming Concepts
Show steps
Strengthen your foundation by revisiting fundamental programming concepts, such as variables, data types, and control structures.
Browse courses on
Programming Concepts
Show steps
-
Refer to textbooks or online resources that cover basic programming.
-
Practice writing simple programs to reinforce your understanding.
Two other activities
Expand to see all activities and additional details
Show all five activities
Practice Python Exercises
Show steps
Reinforce your understanding of Python basics by practicing exercises involving syntax, control structures, and data structures.
Browse courses on
Python
Show steps
-
Find online coding platforms or exercises.
-
Start solving exercises related to the topics covered in the course.
-
Review the solutions and identify areas for improvement.
Build a Mini Python Project
Show steps
Apply your Python skills by building a small project that demonstrates your knowledge and creativity.
Show steps
-
Identify a problem or idea that can be solved using Python.
-
Design and plan the project, including the functionality and user interface.
-
Develop the project using Python, implementing the necessary code and algorithms.
-
Test and debug the project to ensure it functions correctly.
Organize Course Materials
Show steps
Establish a structured approach by organizing notes, assignments, quizzes, and exams for easy reference and review.
Show steps
Show steps
Show steps
- Create folders or use a note-taking app to categorize materials.
- Review materials regularly to reinforce your understanding.
Revisit Python Syntax
Show steps
Ensure familiarity with Python's syntax by reviewing the core syntax elements, such as keywords, operators, and indentation.
Browse courses on
Python Syntax
Show steps
Show steps
Show steps
- Go through the course materials or online tutorials that cover Python syntax.
- Practice writing simple Python code snippets to refresh your memory.
Review Basic Programming Concepts
Show steps
Strengthen your foundation by revisiting fundamental programming concepts, such as variables, data types, and control structures.
Browse courses on
Programming Concepts
Show steps
Show steps
Show steps
- Refer to textbooks or online resources that cover basic programming.
- Practice writing simple programs to reinforce your understanding.
Two other activities
Expand to see all activities and additional details
Show all five activities
Practice Python Exercises
Show steps
Reinforce your understanding of Python basics by practicing exercises involving syntax, control structures, and data structures.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find online coding platforms or exercises.
- Start solving exercises related to the topics covered in the course.
- Review the solutions and identify areas for improvement.
Build a Mini Python Project
Show steps
Apply your Python skills by building a small project that demonstrates your knowledge and creativity.
Show steps
Show steps
Show steps
- Identify a problem or idea that can be solved using Python.
- Design and plan the project, including the functionality and user interface.
- Develop the project using Python, implementing the necessary code and algorithms.
- Test and debug the project to ensure it functions correctly.
Career center
Learners who complete Python Power Up: Coding Foundations for Data Wizards will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
As a Data Scientist at various companies such as Google, Amazon, and Facebook, you examine and analyze data using machine learning and statistical techniques to extract insights that help businesses make informed decisions. Python is a significant part of the Data Scientist's toolkit. This course provides a solid foundation in Python and its essential data structures for any data scientist looking to excel in the field.
Data Analyst
Data Analyst
Data Analysts in organizations of all sizes explore data to identify patterns and trends from a data set. They collect and analyze raw data, translate the data into understandable formats, and present it to help companies make informed decisions. This course introduces Python, a must-have tool for any data analyst, and its essential data structures.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models that power a variety of applications, from search engines to self-driving cars. Familiarity with Python is key for Machine Learning Engineers. This course provides a crucial foundation for any aspiring Machine Learning Engineer.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers take raw data and turn it into visual representations, charts, and graphs. Proficiency in Python is a key skill for Data Visualization Engineers. This course can help build a foundation in Python and its essential data structures for aspiring Data Visualization Engineers.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. Many industries employ these professionals, from finance to healthcare. Python is commonly used in software engineering, and this course may be useful in building a strong foundation in the language and its data structures.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. They ensure that the data is stored and organized appropriately. A sound understanding of data structures and Python are both helpful skills for Database Administrators to have. This course provides a foundation in both of these areas and can be useful in a career as a Database Administrator.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to provide insights that help organizations make better decisions. They often work with large amounts of data, which they analyze to identify trends and patterns. Python is a useful tool for Business Intelligence Analysts, and this course may be helpful in developing a foundational understanding of Python and its data structures.
Financial Analyst
Financial Analyst
Financial Analysts evaluate and interpret financial data to make investment recommendations. This work typically requires a background in mathematics and finance, but Python is increasingly used in finance. This course can help build a foundation in Python and its essential data structures, which may be useful for Financial Analysts.
Information Security Analyst
Information Security Analyst
Information Security Analysts protect computer networks and systems from cyberattacks. They work with various tools and technologies to find vulnerabilities and implement security measures. A foundational understanding of Python and its data structures can be helpful. This course provides a stepping stone towards building this foundation.
Actuary
Actuary
Actuaries use mathematics and statistics to assess the financial impact of risk and uncertainty. They typically work in the insurance and finance industries. While not a requirement, Python is increasingly used by Actuaries. This course may be helpful in developing a foundational understanding of the language and its data structures.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present statistical data. They work in a variety of industries, including government, healthcare, and business. Python is becoming increasingly used by Statisticians, and this course may be useful in building a basic understanding of the language and its data structures.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This role typically requires a strong background in mathematics and statistics. Some Operations Research Analysts also use Python in their work. This course may be helpful in developing a foundational understanding of the language and its data structures, which could be an asset to aspiring Operations Research Analysts.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks within organizations. Many industries employ Risk Analysts, including finance, insurance, and healthcare. This course can help build foundational knowledge in Python and its essential data structures, which may be useful for aspiring Risk Analysts.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts apply mathematical and statistical techniques to financial data. They typically work in the finance industry, where Python is increasingly used. This course may be useful in developing a foundational understanding of the language and its data structures, which could be an asset to aspiring Quantitative Analysts.
Market Researcher
Market Researcher
Market Researchers gather and analyze data about consumer behavior. They use this information to help businesses make informed marketing decisions. This course can help build a strong foundation in Python and its essential data structures, which may be useful for Market Researchers.
For more career information including salaries, visit:
OpenCourser.com/course/oatxw9/python
Reading list
We've selected 24 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Python Power Up: Coding Foundations for Data Wizards.
This book, written in the same language as the course, serves as a supplemental reading to the course. It delves into Python programming with a practical, hands-on approach that complements the course's focus on Python basics and foundational concepts.
Covers the basics of Python programming as well as how to use Python for data science.
Provides a comprehensive overview of data structures, algorithms, and their applications in Python. It aligns well with the course's objective to cover data structures, algorithms, and their complexity analysis.
Provides a comprehensive overview of Python programming for bioinformatics.
Save
Offers a visual, intuitive approach to understanding algorithms and their concepts. It complements the course's introduction to algorithms by providing a more in-depth exploration of algorithmic problem-solving.
Covers the basics of Python programming and good starting point for those new to the language.
Provides a comprehensive overview of data structures and algorithms in Python.
Save
Provides a comprehensive overview of Python programming.
Provides a hands-on introduction to data science using Python.
Provides a comprehensive overview of machine learning using Python.
Save
Provides a comprehensive overview of data analytics using Python.
Provides a comprehensive overview of Python programming for finance.
Provides a comprehensive overview of Python programming for web development.
This beginner-friendly book introduces Python programming through practical projects and examples. While it doesn't directly align with the course's focus on data science, it provides a solid foundation in Python, which is essential for the course's content.
Provides a comprehensive overview of algorithms and data structures.
Save
Provides a gentle introduction to programming concepts like variables, data structures, and functions. It aligns well with the course's objective to introduce Python basics and programming fundamentals.
Provides a hands-on approach to learning Python programming.
Focuses on Python's applications in data analysis and manipulation. While it goes beyond the scope of the course, it provides a valuable introduction to essential Python libraries for data science.
Save
Offers practical advice and best practices for writing efficient and effective Python code. It complements the course by providing additional guidance on Python programming techniques.
This comprehensive textbook provides a rigorous and in-depth exploration of algorithms and their analysis. While it might be more advanced than the course's introductory level, it serves as a valuable reference for further exploration of algorithms.
Save
This comprehensive reference provides a detailed overview of Python syntax, libraries, and tools. It serves as a valuable companion to the course, offering a quick and easy way to look up Python-specific information.
Save
This visually engaging book introduces Python programming through interactive exercises and puzzles. While it covers similar topics as the course, it provides a more accessible and fun approach to learning.
Save
Delves into the nuances and intricacies of Python programming. While it assumes some familiarity with Python, it provides insights and best practices that can enhance the skills of those taking the course.
Save
This comprehensive guide provides a thorough foundation in Python programming. While it covers more advanced topics than the course, it serves as a valuable reference for those seeking a deeper understanding of Python.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/oatxw9/python
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Effort
8 to 12 hours per week for 5 weeks
Level
Introductory
Via
edX
Institution
Xccelerate
Instructor
Avishek Majumder
Session
June 4, 2024
- February 21, 2025
Language
English
Transcript
English
Good to know
Develops Python programming essentials, data structures, and algorithmic thinking, which are core skills for data science
Taught by Avishek Majumder, who is recognized for his work in data science and Python programming
Emphasizes practical skills through hands-on labs and interactive materials
Builds a strong foundation for beginners, providing a comprehensive introduction to Python for data science
Requires students to come in with no prior programming experience
Focuses on essential Python libraries for data science, such as NumPy and Pandas
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