Este curso forma parte de Programa especializado: AI For Business

4.7
estrellas
79 calificaciones

Kartik Hosanagar +1 instructores más

5762 ya inscrito

Ofrecido Por

Programa especializado: AI For BusinessUniversidad de Pensilvania

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In this course, you will go in-depth to discover how Machine Learning is used to handle and interpret Big Data. You will get a detailed look at the various ways and methods to create algorithms to incorporate into your business with such tools as Teachable Machine and TensorFlow. You will also learn different ML methods, Deep Learning, as well as the limitations but also how to drive accuracy and use the best training data for your algorithms. You will then explore GANs and VAEs, using your newfound knowledge to engage with AutoML to help you start building algorithms that work to suit your needs. You will also see exclusive interviews with industry leaders, who manage Big Data for companies such as McDonald's and Visa. By the end of this course, you will have learned different ways to code, including how to use no-code tools, understand Deep Learning, how to measure and review errors in your algorithms, and how to use Big Data to not only maintain customer privacy but also how to use this data to develop different strategies that will drive your business.

Fechas límite flexibles

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Curso 1 de 4 en

Programa especializado: AI For Business

Aprox. 7 horas para completar

Inglés (English)

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 1 de 4 en

Programa especializado: AI For Business

Aprox. 7 horas para completar

Inglés (English)

Instructores

Calificación del instructor

4,91/5 (40 calificaciones)

Kartik Hosanagar

Prasanna Tambe

Associate Professor of Operations

Information and Decisions

7576 alumnos

3 cursos

Ofrecido por

Universidad de Pensilvania

Programa - Qué aprenderás en este curso

Semana1

Semana 1

3 horas para completar

Module 1 – Big Data and Artificial Intelligence

In this module, you will be introduced to Big Data and examine how machine learning is used throughout various business segments. You will also learn how data is analyzed and extracted, and how digital technologies have been used to expand and transform businesses. You will also get a detailed look at data management tools and how they are best implemented and the value of data warehouses. By the end of this module, you will have gained insight into how machine learning can be used as a general-purpose technology, and some best techniques and practices for data mining.

3 horas para completar

11 videos (Total 93 minutos), 1 lectura, 1 cuestionario

11 videos

AI for Business Introduction8mCourse Introduction1mBig Data Overview9mBig Data Analysis5mData Management Tools7mData Management Infrastructure9mData Analysis: Extracting Intelligence from Big Data10mIntroduction to Artificial Intelligence9mMachine Learning Overview15mReinforcement Learning7mA Detailed View of Machine Learning7m

1 lectura

Module 1 Slides30m

1 ejercicio de práctica

Module 1 Quiz30m

Semana2

Semana 2

2 horas para completar

Module 2 – Training and Evaluating Machine Learning Algorithms

In this module, you will get an in-depth look at contrasting Machine Learning methods, including logistic regression and neural nets. You will also learn about Deep Learning and its relationship to neural networks and how to best optimize Machine Learning algorithms. Lastly, you will be introduced to loss functions and how to best measure and review errors to maintain the integrity of your algorithms. By the end of this module, you will have learned about Machine Learning methods, the limitations and value of Deep Learning, how best to drive precision and accuracy in algorithms, and how to get the best training data for those algorithms.

2 horas para completar

13 videos (Total 74 minutos), 1 lectura, 1 cuestionario

13 videos

Specific Machine Learning Methods: A Deep Dive18mIntro to Model Selection3mFeature Engineering and Deep Learning Introduction3mDeep Learning6mHow Deep Learning Works8mLimitations of Deep Learning2mEvaluating ML Performance3mCommon Loss Functions5mTradeoffs Between Loss Functions2mHow is Training Data Acquired?4mThe Over-Fitting Problem5mTest Data3mExamples of End-to-End Work Flow4m

1 lectura

Module 2 Slides30m

1 ejercicio de práctica

Module 2 Quiz30m

Semana3

Semana 3

1 hora para completar

Module 3 – ML Application and Emerging Methods

In this module, you will take a look at Machine Learning within natural language processing and using generative modeling to create new data. You will also focus on AutoML and how to best utilize automated processes to make your algorithms more efficient. You will also review the no-code Machine Learning tool Teachable Machine, which serves to make Deep and Machine Learning more accessible. By the end of this module, you will be able to use AutoML in your algorithms and be able to navigate and use Teachable Machine in practice for no-code solutions to building an algorithm.

1 hora para completar

8 videos (Total 45 minutos), 1 lectura, 1 cuestionario

Semana4

Semana 4

1 hora para completar

Module 4 - Industry Interview

In this module, you will hear from an industry leader and gain valuable insight into data sampling and building realistic usable models. Ed Lee, VP of Global Menu Strategy & Global Marketing at McDonald's, will allow you to review real-world solutions and how they handle data issues as one of the most successful global brands. By the end of this module, you will have heard from a top industry expert in their field and gained firsthand knowledge and understanding of how Big Data plays into maintaining privacy in data and also utilizing that data to enhance your marketing, content, and refine your algorithms.

1 hora para completar

1 video (Total 13 minutos)

Reseñas

4.7

18 reseña

5 stars
80,95 %
4 stars
13,09 %
3 stars
1,19 %
2 stars
1,19 %
1 star
3,57 %

Principales reseñas sobre AI FUNDAMENTALS FOR NON-DATA SCIENTISTS

por BF21 de oct. de 2021

Excellent introduction to the basic concepts of using AI and Machine Learning in a business context.

por CD2 de dic. de 2022

The format of this course of great for working parents who are complete novices about AI!

por SS19 de sep. de 2022

This is a very insightful course that offers a comprehensive understanding of AI concepts in a systematic way to individuals from any domain.

por CL6 de sep. de 2022

This course is very interesting and well presented.

Ver todas las reseñas

Acerca de Programa especializado: AI For Business

This specialization will provide learners with the fundamentals of using Big Data, Artificial Intelligence, and Machine Learning and the various areas in which you can deploy them to support your business. You'll cover ethics and risks of AI, designing governance frameworks to fairly apply AI, and also cover people management in the fair design of HR functions within Machine Learning. You'll also learn effective marketing strategies using data analytics, and how personalization can enhance and prolong the customer journey and lifecycle. Finally, you will hear from industry leaders who will provide you with insights into how AI and Big Data are revolutionizing the way we do business.

By the end of this specialization, you will be able to implement ethical AI strategies for people management and have a better understanding of the relationship between data analytics, artificial intelligence, and machine learning. You will leave this specialization with insight into how these tools can shape and influence how you manage your business. For additional reading, Professor Hosanagar's book "A Human’s Guide to Machine Intelligence" can be used as an additional resource,". You can find Professor Hosanagar's book on his personal website or at Penguin Randomhouse.

Preguntas Frecuentes

¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
Si estás suscrito, obtienes una prueba gratis de 7 días, que podrás cancelar cuando desees sin ningún tipo de penalidad. Una vez transcurrido ese tiempo, no realizamos reembolsos. No obstante, puedes cancelar tu suscripción cuando quieras. Consulta nuestra política completa de reembolsos.
¿Hay ayuda económica disponible?
Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.

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AI Fundamentals for Non-Data Scientists

Acerca de este Curso