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Python Fundamentals for Business Analytics

Catherine Ridings

The course will illustrate how Python is utilized in the exciting field of business analytics through real-world examples and hands-on exercises. With an emphasis on interactivity, students will code alongside the course materials. By the end of this course, students will have developed a strong understanding of programming principles, gained proficiency in Python syntax, and developed the skill to apply Python functions to basic analytic problems.

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What's inside

Learning objective

Upon completion of this course, students should be able to:1. install and use the anaconda distribution of python through the creation of jupyter notebooks.2. understand and use variables in python3. work with common python data types including float, integer, string, boolean, lists, and tuples4. create expression in python with variables, relational operators, and boolean operators5. implement basic program flow control with if statements and loops6. read data from and write data to text files.7. utliize important analytic libraries like numpy8. understand how to implement and adequately test algorithms in python

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces Python programming, which is a must-have for professionals in the data science sector

Provides practical training in data analytics using real-world examples, enabling a deep understanding of business-related issues

Develops foundational Python programming skills, such as syntax and data types, which serves as a solid stepping stone for advanced data analytics

Focuses on analyzing data in text files, a common task in business analytics, allowing learners to extract insights effectively

Leverages reputable libraries like NumPy, a cornerstone in the data analytics domain, providing learners with essential tools

Emphasizes algorithm implementation, a core skill for data scientists, and includes testing practices to ensure accuracy

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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 Fundamentals for Business Analytics with these activities:

Join a Python Study Group

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Collaborate with peers to reinforce concepts and gain diverse perspectives.

Browse courses on Python Programming

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Find a study group or create your own
Meet regularly to discuss course materials
Work on practice problems together
Provide feedback and support to each other

Review Python Basics

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Review the fundamentals of Python to ensure a solid foundation for the course.

Browse courses on Python Syntax

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Review online tutorials on Python basics
Complete practice exercises on basic Python concepts
Set up your Python development environment

Read 'Python for Data Analysis'

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Gain in-depth knowledge of Python's capabilities for data analysis.

View Python for Data Analysis on Amazon

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Read the book thoroughly
Take notes and highlight important concepts
Work through the exercises and examples provided in the book

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Explore NumPy and Pandas Libraries

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Become familiar with essential Python libraries for data analysis.

Browse courses on NumPy

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Follow online tutorials on NumPy and Pandas
Practice using these libraries in Jupyter notebooks
Build a small project using NumPy and Pandas

Solve Python Coding Challenges

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Enhance your Python problem-solving skills through practice.

Browse courses on Python Programming

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Solve coding challenges on platforms like LeetCode or HackerRank
Participate in Python coding competitions
Implement Python algorithms and data structures

Develop a Data Visualization Dashboard

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Apply Python to create an interactive dashboard that displays business insights.

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Gather and clean the necessary data
Choose appropriate visualization techniques
Use Python libraries to create interactive dashboards
Deploy the dashboard and share insights

Contribute to Open Source Python Projects

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Gain practical experience by contributing to real-world Python projects.

Browse courses on Python Programming

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Find open source Python projects on GitHub or other platforms
Identify areas where you can contribute
Submit pull requests with your contributions
Collaborate with other developers

Participate in a Python Hackathon

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Challenge yourself by solving real-world problems using Python in a competitive setting.

Browse courses on Python Programming

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Find a relevant hackathon
Form a team or participate individually
Develop a solution using Python
Present your solution and compete for prizes

Career center

Learners who complete Python Fundamentals for Business Analytics will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use their skills in programming, machine learning, and statistics to analyze data and help businesses make better decisions. This course provides a strong foundation in Python, which is one of the most popular programming languages for data analysis. The course also covers essential data analysis concepts such as data cleaning, data visualization, and statistical modeling. Completing this course will give you the skills and knowledge you need to succeed as a Data Analyst.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts use their skills in data analysis, problem-solving, and communication to help businesses improve their operations. This course provides a strong foundation in Python, which is a valuable tool for Business Analysts. The course also covers essential business analysis concepts such as process improvement, data modeling, and financial analysis. Completing this course will give you the skills and knowledge you need to succeed as a Business Analyst.

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Quantitative Analyst

Quantitative Analysts use their skills in mathematics, statistics, and programming to develop and implement financial models. This course provides a strong foundation in Python, which is one of the most popular programming languages for quantitative finance. The course also covers essential quantitative finance concepts such as risk management, portfolio optimization, and algorithmic trading. Completing this course will give you the skills and knowledge you need to succeed as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts use their skills in finance, accounting, and economics to analyze financial data and make investment recommendations. This course provides a strong foundation in Python, which is a valuable tool for Financial Analysts. The course also covers essential financial analysis concepts such as financial statement analysis, valuation, and portfolio management. Completing this course will give you the skills and knowledge you need to succeed as a Financial Analyst.

See salaries and explore the career path for Financial Analyst

Machine Learning Engineer

Machine Learning Engineers use their skills in programming, machine learning, and statistics to develop and implement machine learning models. This course provides a strong foundation in Python, which is one of the most popular programming languages for machine learning. The course also covers essential machine learning concepts such as supervised learning, unsupervised learning, and deep learning. Completing this course will give you the skills and knowledge you need to succeed as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use their skills in programming, machine learning, and statistics to extract insights from data. This course provides a strong foundation in Python, which is one of the most popular programming languages for data science. The course also covers essential data science concepts such as data mining, data visualization, and statistical modeling. Completing this course will give you the skills and knowledge you need to succeed as a Data Scientist.

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Software Engineer

Software Engineers use their skills in programming, software design, and software development to develop and implement software applications. This course provides a strong foundation in Python, which is one of the most popular programming languages for software development. The course also covers essential software engineering concepts such as object-oriented programming, design patterns, and software testing. Completing this course will give you the skills and knowledge you need to succeed as a Software Engineer.

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Web Developer

Web Developers use their skills in programming, web design, and web development to develop and implement websites and web applications. This course provides a strong foundation in Python, which is one of the most popular programming languages for web development. The course also covers essential web development concepts such as HTML, CSS, and JavaScript. Completing this course will give you the skills and knowledge you need to succeed as a Web Developer.

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Data Engineer

Data Engineers use their skills in programming, data management, and data engineering to design and implement data pipelines. This course provides a strong foundation in Python, which is one of the most popular programming languages for data engineering. The course also covers essential data engineering concepts such as data integration, data transformation, and data quality. Completing this course will give you the skills and knowledge you need to succeed as a Data Engineer.

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Statistician

Statisticians use their skills in probability, statistics, and data analysis to collect, analyze, and interpret data. This course provides a strong foundation in Python, which is a valuable tool for Statisticians. The course also covers essential statistics concepts such as descriptive statistics, inferential statistics, and regression analysis. Completing this course will give you the skills and knowledge you need to succeed as a Statistician.

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Actuary

Actuaries use their skills in mathematics, statistics, and finance to assess risk and uncertainty. This course provides a strong foundation in Python, which is a valuable tool for Actuaries. The course also covers essential actuarial concepts such as risk management, insurance, and financial analysis. Completing this course will give you the skills and knowledge you need to succeed as an Actuary.

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Market Researcher

Market Researchers use their skills in research, data analysis, and marketing to understand consumer behavior and trends. This course provides a strong foundation in Python, which is a valuable tool for Market Researchers. The course also covers essential market research concepts such as survey design, data analysis, and market segmentation. Completing this course will give you the skills and knowledge you need to succeed as a Market Researcher.

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Financial Planner

Financial Planners use their skills in finance, investing, and financial planning to help clients achieve their financial goals. This course provides a strong foundation in Python, which can be useful for certain aspects of financial planning, such as data analysis and financial modeling.

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Investment Analyst

Investment Analysts use their skills in finance, investing, and financial analysis to evaluate investment opportunities. This course provides a strong foundation in Python, which can be useful for certain aspects of investment analysis, such as data analysis and financial modeling.

See salaries and explore the career path for Investment Analyst

Risk Analyst

Risk Analysts use their skills in risk management, finance, and data analysis to identify and assess risks. This course provides a strong foundation in Python, which can be useful for certain aspects of risk analysis, such as data analysis and financial modeling.

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Reading list

We've selected 14 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 Fundamentals for Business Analytics.

Python for Data Analysis

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Great resource for learning how to use Python for data analysis. It covers all the basics of Python, including data types, data structures, and control flow. It also covers more advanced topics such as data visualization, machine learning, and natural language processing.

Python Fundamentals for Business Analytics

What's inside

Learning objective

Good to know

Save this course

Activities

Career center

Reading list

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