RH, Dados e Inteligência Artificial from Coursera

Nossas boas-vindas ao Curso RH, Dados e Inteligência Artificial.

Neste curso, você aprenderá que a transformação digital na área de Recursos Humanos é a reorganização e a remodelagem das funções de gestão de pessoas, utilizando a tecnologia para recriar sistemas operacionais e processos eficientes, que inclui substituir ou não os sistemas tradicionais para todas as áreas.

Podemos resumir como: uma mudança de mentalidade que as empresas passam com o objetivo de se tornarem mais modernas e acompanharem os avanços tecnológicos que não param de surgir, como Internet das Coisas (IoT), computação em nuvem, Big Data, Inteligência Artificial e os robôs.

O curso aborda os principais temas do mercado de dados aplicado à área de Recursos Humanos.

Ao final deste curso, você será capaz de entender temas como:

- Transformação digital em RH;

- As etapas para se tornar orientado por dados;

- Desafios do RH orientado por dados;

- Fundamentos de Inteligência Artificial;

- Aprendizado de máquina;

- Aplicações de modelos.

Este curso é composto por quatro módulos, disponibilizados em semanas de aprendizagem. Cada módulo é composto por vídeos, leituras e testes de verificação de aprendizagem. Ao final de cada módulo, temos uma avaliação de verificação dos conhecimentos.

Estamos muito felizes com sua presença neste curso e esperamos que você tire o máximo de proveito dos conceitos aqui apresentados.

Bons estudos!

What's inside

Syllabus

Transformação Digital em RH

A transformação digital no departamento de Recursos Humanos é a reorganização e remodelagem das funções de conciliação entre empresa e colaboradores, utilizando a tecnologia para recriar sistemas operacionais e processos eficientes, que inclui substituir ou não os sistemas tradicionais para todas as áreas do negócio. Quando falamos especificamente da área de Recursos Humanos, é uma mudança de paradigma na qual se utilizam dados para orientar todo os processos de decisão como: Folha de pagamento, benefícios, gestão de desempenho, recompensas e processos de contratação.

Fundamentos de Inteligência Artificial

A Inteligência Artificial (IA) já está presente em nossas vidas. É utilizada desde o momento em que desbloqueamos nosso smartphone utilizando reconhecimento facial, respondemos a um e-mail ou acessamos nossas redes sociais preferidas. De forma bem simples, a IA é constituída por programas de computadores que imitam a maneira como os humanos aprendem e resolvem problemas complexos. Computadores com IA são programados para aprender atividades como reconhecimento de fala, reconhecimento visual, identificação de padrões, resolução de problemas e planejamento de tarefas.

Aprendizado de Máquina

De forma bem simples, o aprendizado de máquina nos permite usar algoritmos de computador para construir modelos que podem fazer previsões, descobrir padrões ou resolver problemas. Porém, não vamos dizer, explicitamente, como o computador fará isso. O algoritmo de aprendizado de máquina utilizará uma grande variedade de dados, estruturados e não-estruturados para aprender com esses dados e realizar suas previsões.

Aplicações de Modelos

A área de Machine Learning está em constante evolução. Por isso, é necessário entender cada componente utilizado em cada tipo de projeto e como podemos analisar os impactos e obter o melhor retorno para essa abordagem.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Este curso é exclusivo para profissionais de RH que buscam se aprimorar no uso de dados e inteligência artificial

Ensina fundamentos de inteligência artificial, aprendizado de máquina e aplicações de modelos

Desenvolvido por Anderson França, especialista em RH, dados e inteligência artificial

Oferece uma abordagem prática, com vídeos, leituras e testes de verificação de aprendizagem

Requer conhecimento prévio em gestão de recursos humanos

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 RH, Dados e Inteligência Artificial with these activities:

Review the basics of data management

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Start by reviewing the basics of data management to ensure you have a strong foundation for the topics covered in this course.

Browse courses on Data Management

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Review key concepts of data management, such as data types, data structures, and data integrity.
Practice organizing and structuring data in different ways.
Review techniques for cleaning and preparing data for analysis.

Join a study group or online forum

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Engaging with peers can provide valuable perspectives and help you identify areas where you need additional support.

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Find a study group or online forum related to the course topics.
Participate regularly in discussions and ask questions.
Help other learners by sharing your knowledge and insights.

Solve data analysis practice problems

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Regular practice is crucial for improving your data analysis skills.

Browse courses on Data Analysis

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Find online platforms or textbooks that provide data analysis practice problems.
Set aside time each week to solve practice problems.
Review your solutions and identify areas for improvement.

Five other activities

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Follow online tutorials on machine learning

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There are numerous free and paid online tutorials available that can help you learn about machine learning.

Browse courses on Machine Learning

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Identify specific machine learning topics that you want to learn or improve.
Search for online tutorials from reputable sources.
Follow the tutorials step-by-step and complete any practice exercises.

Volunteer as a tutor or mentor

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Helping others can solidify your understanding of the course concepts and develop your communication skills.

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Identify opportunities to volunteer as a tutor or mentor in your community or online.
Prepare materials and lesson plans to support learners.
Provide guidance and support to learners, answering their questions and helping them overcome challenges.

Write a blog post or article on a data analysis topic

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Writing about data analysis will help you internalize the concepts and share your knowledge with others.

Browse courses on Data Analysis

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Identify a specific data analysis topic that you are knowledgeable about.
Research the topic thoroughly to ensure accuracy and depth of understanding.
Outline the key points you want to cover in your writing.
Write a clear and engaging blog post or article that explains the topic to your target audience.
Share your writing with others and seek feedback to improve your communication skills.

Develop a data-driven solution for a business problem

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Applying your learning to a real-world problem will reinforce your understanding and demonstrate your skills to potential employers.

Browse courses on Data-Driven Decision Making

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Identify a business problem that can be addressed using data.
Gather and analyze relevant data.
Develop a data-driven solution to the problem.
Present your solution in a clear and concise manner.
Get feedback on your solution and iterate as necessary.

Contribute to open-source projects related to data analysis

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Contributing to open-source projects provides practical experience and allows you to collaborate with others in the field.

Browse courses on Data Analysis

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Identify open-source projects related to data analysis that align with your interests.
熟悉项目的代码库和文档。
Identify areas where you can contribute, such as bug fixes, feature improvements, or documentation updates.
Make your contributions and submit pull requests.
Engage with the project community and seek feedback on your contributions.

Career center

Learners who complete RH, Dados e Inteligência Artificial will develop knowledge and skills that may be useful to these careers:

Data Analyst

The course is named RH, Dados e Inteligência Artificial, and it is designed to teach the core principles needed by anyone who wants to work as a Data Analyst. Most of the top employers for this profession require a bachelor's degree in Computer Science, Data Science, Statistics, or a related field. The course covers topics like data transformation, data visualization, and machine learning, which will help students build a strong foundation in the fundamental skills of a Data Analyst.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

A Machine Learning Engineer is someone who designs, develops, and deploys machine learning models. The course covers topics like supervised and unsupervised learning, natural language processing, and computer vision, which will help students build a strong foundation in the skills needed by a Machine Learning Engineer. Most of the top employers require a master's degree or higher in a related field like Computer Science, Statistics, or Software Engineering.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

The course covers topics like data mining, data visualization, and big data, which will help students build a strong foundation in the skills needed by a Data Scientist. Most of the top employers for this profession require a master's degree or higher in a related field like Computer Science, Statistics, or Mathematics.

See salaries and explore the career path for Data Scientist

Business Analyst

The course covers topics like data analysis, business intelligence, and project management, which will help students build a strong foundation in the skills needed by a Business Analyst. Most of the top employers require a bachelor's degree in Business Administration, Information Technology, or a related field.

See salaries and explore the career path for Business Analyst

Financial Analyst

The course covers topics like financial modeling, financial analysis, and investment management, which will help students build a strong foundation in the skills needed by a Financial Analyst. Most of the top employers require a bachelor's degree in Finance, Economics, or a related field.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

The course covers topics like linear programming, simulation, and optimization, which will help students build a strong foundation in the skills needed by an Operations Research Analyst. Most of the top employers require a bachelor's degree in Operations Research, Industrial Engineering, or a related field.

See salaries and explore the career path for Operations Research Analyst

Statistician

The course covers topics like probability, statistics, and data analysis, which will help students build a strong foundation in the skills needed by a Statistician. Most of the top employers require a bachelor's degree in Statistics, Mathematics, or a related field.

See salaries and explore the career path for Statistician

Software Developer

The course covers topics like object-oriented programming, data structures, and algorithms, which will help students build a strong foundation in the skills needed by a Software Developer. While most of the top roles require a bachelor's degree in Computer Science or a related field, there are many who have transitioned into the field from other backgrounds by completing courses like this one.

See salaries and explore the career path for Software Developer

Market Researcher

The course covers topics like data analysis, market research, and consumer behavior, which will help students build a strong foundation in the skills needed by a Market Researcher. Most of the top employers require a bachelor's degree in Marketing, Business Administration, or a related field.

See salaries and explore the career path for Market Researcher

Data Engineer

The course covers topics like data warehousing, data integration, and big data, which will help students build a strong foundation in the skills needed for a Data Engineer. Most of the top employers require a bachelor's degree in Computer Science, Information Technology, or a related field.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

The course covers topics like financial modeling, time series analysis, and risk management, which will help students build a strong foundation in the skills needed by a Quantitative Analyst. Most of the top employers require a master's degree or higher in a related field like Finance, Mathematics, or Statistics.

See salaries and explore the career path for Quantitative Analyst

Actuary

The course covers topics like probability, statistics, and risk management, which will help students build a strong foundation in the skills needed by an Actuary. Most of the top employers require a bachelor's degree in Actuarial Science, Mathematics, or a related field.

See salaries and explore the career path for Actuary

Risk Manager

The course covers topics like risk management, financial modeling, and data analysis, which will help students build a strong foundation in the skills needed by a Risk Manager. Most of the top employers require a bachelor's degree in Finance, Risk Management, or a related field.

See salaries and explore the career path for Risk Manager

Information Security Analyst

The course covers topics like information security, risk management, and data protection, which will help students build a strong foundation in the skills needed for an Information Security Analyst. Most of the top employers require a bachelor's degree in Information Technology, Computer Science, or a related field.

See salaries and explore the career path for Information Security Analyst

Data Protection Officer

The course covers topics like data protection, privacy regulations, and information security, which will help students build a strong foundation in the skills needed for a Data Protection Officer. Most of the top employers require a bachelor's degree in Information Technology, Computer Science, or a related field.

See salaries and explore the career path for Data Protection Officer