Python para a Ciência de Dados e IA from Coursera

Inicie seu estudo de Python para ciência de dados e de programação em geral com esta introdução ao Python feita especialmente para iniciantes. Python é uma das linguagens de programação mais populares do mundo e nunca houve tanta demanda por profissionais com a habilidade de aplicar os princípios básicos de Python para impulsionar soluções de negócios em vários setores. Neste curso, você aprenderá do zero a programar com Python em questão de horas, sem precisar ter experiência prévia em programação! Você aprenderá os fundamentos básicos de Python, incluindo estruturas e análise de dados, exercícios práticos em todo os módulos do curso e criará um projeto final para demonstrar suas novas habilidades. Até o final deste curso, você vai se sentir confiante para criar programas básicos, trabalhar com dados e resolver problemas do mundo real com Python. Você terá uma base de conhecimento forte para fazer estudos mais avançados na área e desenvolverá habilidades para ajudar a subir na sua carreira. Este curso pode ser aplicado em várias especializações ou programas de certificação profissional. Concluir este curso contará para o seu aprendizado em qualquer um dos programas a seguir: Certificado Profissional de IA Aplicada da IBAM Especialização em Ciências de Dados Aplicada Certificado Profissional em Ciência de Dados da IBM Após a conclusão de um dos programas acima, além de ganhar um certificado de conclusão de especialização da Coursera, você também receberá um selo digital da IBM reconhecendo a sua competência na área.

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Examines the fundamentals of programming in Python, using concepts relevant to science and data analysis

Provides an accessible introduction to Python for beginners with no prior programming experience

Offers a strong foundation for further studies in data science

Taught by recognized instructors

Includes practical exercises and a final project, allowing learners to apply their skills

Reviews summary

Beginner-friendly python course

This beginner-friendly course is a solid introduction to Python for those with no prior programming experience. It covers the basics of Python, including data structures and analysis, with practical exercises and a final project to demonstrate your skills. However, some videos lack Portuguese subtitles as advertised.

Great for beginners with no programming experience

"Você aprenderá do zero a programar com Python em questão de horas, sem precisar ter experiência prévia em programação!"

Some videos lack Portuguese subtitles as advertised

"Dizia ter legendas em portugues(Brasil) mas nao tem em todos os videos"

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 para a Ciência de Dados e IA with these activities:

Review Python Crash Course

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Build a strong foundation in Python by reviewing this comprehensive introductory book.

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Read the Introduction and Chapter 1.
Complete the exercises in Chapter 1.
Review the material by summarizing key points.

Follow an online tutorial on Python data visualization

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Enhance understanding of Python data visualization techniques through guided tutorials.

Browse courses on Python Programming

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Find an online tutorial on Python data visualization.
Follow the tutorial step-by-step.
Create a data visualization project using the techniques you learned in the tutorial.

Solve Python coding problems

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Improve problem-solving and coding skills by practicing Python coding problems.

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Find Python coding problems online or in a book.
Solve the problems using Python.
Review your solutions and identify areas for improvement.

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Participate in a Python study group

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Enhance understanding and retention by discussing concepts and working on problems with peers.

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Find a Python study group or create your own.
Attend study group meetings regularly.
Participate in discussions and work on problems together.
Share knowledge and resources with other group members.

Build a Python script to analyze a small dataset

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Apply Python concepts learned in the course to a hands-on project.

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Choose a small dataset to analyze.
Develop a Python script to load and clean the data.
Perform basic data analysis on the data.
Write a report summarizing your findings.

Create a presentation on Python functions

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Reinforce understanding of Python functions by creating a presentation.

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Review the material on Python functions.
Create a presentation that covers the different types of functions, how to define them, and how to use them.
Share your presentation with others.
Get feedback on your presentation.

Volunteer at a local coding organization

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Gain practical experience and support the community by volunteering at a local coding organization.

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Find a local coding organization that offers volunteer opportunities.
Contact the organization and express your interest in volunteering.
Attend volunteer training.
Assist with coding projects or other activities.

Participate in a coding competition

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Challenge yourself, improve problem-solving skills, and showcase your Python abilities.

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Find a coding competition that is relevant to Python.
Prepare for the competition by practicing Python coding problems.
Participate in the competition and try your best to solve the problems.
Review your performance and identify areas for improvement.

Career center

Learners who complete Python para a Ciência de Dados e IA will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts use their skills in data analysis and visualization to help businesses make better decisions. They collect, clean, and analyze data to identify trends and patterns. They also develop visualizations that can communicate insights to stakeholders. This course in Python for Data Science and AI would help a Data Analyst develop a strong foundation in Python, which is commonly used for data analysis. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. They work with data scientists to identify the right data sources and develop algorithms that can be used to solve specific business problems. They also work with software engineers to integrate machine learning models into existing systems. This course in Python for Data Science and AI would help a Machine Learning Engineer develop a strong foundation in Python, which is used throughout the machine learning lifecycle. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and machine learning.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists develop and deploy machine learning models to solve complex problems. They design and conduct experiments to determine the best data sources for a given task, and build solutions that can be used by businesses to improve their operations. This course in Python for Data Science and AI would help a Data Scientist develop a strong foundation in Python, which can be used for data analysis, machine learning, and other tasks. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and machine learning.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians collect, analyze, and interpret data. They use their skills to help businesses and organizations make better decisions. This course in Python for Data Science and AI may be useful for a Statistician who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Statistician

Software Engineer

Software Engineers design, develop, and maintain software applications. They work with business stakeholders to identify the needs of the application, and then design and develop a solution that meets those needs. They also work with other engineers to integrate the application with existing systems. This course in Python for Data Science and AI may be useful for a Software Engineer who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and machine learning.

See salaries and explore the career path for Software Engineer

Financial Analyst

Financial Analysts use their skills in finance and economics to analyze financial data and make investment recommendations. They work with clients to identify their financial goals, and then develop and implement investment strategies that can help them achieve those goals. This course in Python for Data Science and AI may be useful for a Financial Analyst who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Financial Analyst

Product Manager

Product Managers are responsible for the development and launch of new products and services. They work with engineers, designers, and other stakeholders to define the product vision and roadmap. This course in Python for Data Science and AI may be useful for a Product Manager who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Product Manager

Data Engineer

Data Engineers design, build, and maintain the infrastructure that is used to store and process data. They work with data scientists and other engineers to ensure that data is available and accessible for analysis. This course in Python for Data Science and AI may be useful for a Data Engineer who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. They develop and implement trading strategies, and manage risk. This course in Python for Data Science and AI may be useful for a Quantitative Analyst who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use their skills in mathematics and statistics to assess risk and uncertainty. They work with insurance companies and other financial institutions to develop products and services that can help their clients manage risk. This course in Python for Data Science and AI may be useful for an Actuary who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Actuary

UX Researcher

UX Researchers use their skills in research and design to improve the user experience of products and services. They conduct user research studies to identify pain points and opportunities for improvement. This course in Python for Data Science and AI may be useful for a UX Researcher who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for UX Researcher

Market Researcher

Market Researchers use their skills in research and analysis to help businesses understand their customers and markets. They conduct surveys, interviews, and other research studies to collect data about consumer behavior. This course in Python for Data Science and AI may be useful for a Market Researcher who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Market Researcher

Data Science Manager

Data Science Managers are responsible for leading and managing teams of data scientists. They work with stakeholders to identify the business needs and develop data science strategies. This course in Python for Data Science and AI may be useful for a Data Science Manager who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Data Science Manager

Business Analyst

Business Analysts help businesses improve their operations by analyzing data and identifying opportunities for improvement. They work with stakeholders to understand the business needs, and then develop solutions that can be implemented to improve performance. This course in Python for Data Science and AI may be useful for a Business Analyst who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts use their skills in mathematics and statistics to solve complex problems. They work with businesses and organizations to identify opportunities for improvement, and then develop and implement solutions that can help them achieve their goals. This course in Python for Data Science and AI may be useful for an Operations Research Analyst who wants to develop a strong foundation in Python. The course covers the basics of Python, such as data structures, loops, and functions. It also covers more advanced topics, such as object-oriented programming and data analysis.

See salaries and explore the career path for Operations Research Analyst