大数据 机器学习 人工智能_在这个季节中,您如何免费学习数据科学,人工智能和机器学习。...

(63) 2024-05-28 21:01:03

大数据 机器学习 人工智能

“The more that you read, the more things you will know. The more that you learn, the more places you’ll go.”― Dr. Seuss

“阅读的内容越多,您就会知道的越多。 您学得越多,您就会去的地方越多。”-苏斯博士

We cannot know anything if we do not learn. Choosing to be a data scientist, artificial intelligence, or machine learning engineer practically means you are signing up for a life-long learning journey. A lot of people are doing very amazing things with data science, AI and ML but they all started from somewhere. The beginning stages of learning to become a data scientist, AI, or ML engineer are the toughest since it is at this stage that you meet new things you never knew. Consequently, you’ll just come across advanced methods of doing things and if you have a good understanding of the basics, you would easily excel at the advanced stuff. Every cloud has a silver lining, even though we are in very tough times at the moment, one thing we can be happy about is that we can have lots of learning materials and resources for free. Learning to become a data scientist, AI, or ML engineer is naturally very expensive and as we have it for free now, we have to put in maximum effort to utilize all the good things we can get for as long as it lasts. In this story, I am going to share with you some of the many resources and materials you can access freely if you want to learn to be a data scientist, AI, or ML engineer.

如果我们不学习,我们什么都不知道。 选择成为一名数据科学家,人工智能或机器学习工程师实际上意味着您正在报名参加终身学习之旅。 很多人在数据科学,人工智能和机器学习方面做着非常了不起的事情,但是它们都是从某个地方开始的。 学习成为一名数据科学家,AI或ML工程师的初期阶段最为艰难,因为在此阶段您遇到了未知的新事物。 因此,您只会遇到高级的做事方法,并且如果您对基本知识有很好的了解,那么您将很容易在高级方面有所作为。 每一朵云都有一线希望,即使我们目前处于艰难时期,我们可以高兴的是,我们可以免费获得许多学习资料和资源。 学习成为一名数据科学家,AI或ML工程师自然是非常昂贵的,而且由于我们现在免费提供,因此我们必须尽最大的努力来利用所有可以得到的好东西。 在这个故事中,如果您想学习成为一名数据科学家,人工智能或机器学习工程师,我将与您分享一些您可以自由访问的资源和资料。

GitHub学生开发包 (GitHub Student Developer Pack)

As a student developer, having a GitHub account is very essential. Even so, claiming your GitHub student developer pack is the most important thing you can do in your career as a student developer. The GitHub student developer pack comes with so many goodies that you can access for free for as long as you are a student. The GitHub student developer pack comes with so many software goodies but as someone seeking to learn data science, AI/ML, the most important ones are DataCamp and Educative. These platforms give students free access through the GitHub student developer pack for some months.

作为一名学生开发人员,拥有GitHub帐户非常重要。 即便如此,声称您的GitHub学生开发人员包是您作为学生开发人员的职业中最重要的事情。 GitHub学生开发者包附带了很多东西,只要您是学生,就可以免费访问。 GitHub学生开发者包附带了许多软件功能,但是当有人寻求学习数据科学,AI / ML时,最重要的是DataCamp和Educative 。 这些平台使学生可以通过几个月级的GitHub学生开发者包免费访问。

领英 (LinkedIn)

LinkedIn Learning has made a couple of their paid courses free from now till March 2021. The course Become a Data Analyst is very engaging and guaranteed to get you from beginner to intermediate level in data analysis after completion. You also get a digital badge after completion as certification of course completion.

从即日起至2021年3月,LinkedIn Learning已免费提供了几门付费课程,该课程“ 成为数据分析师”非常吸引人,可以保证您从入门到中级完成数据分析。 完成课程后,您还将获得数字徽章,作为课程结业证书。

Udacity (Udacity)

The AWS machine learning scholarship is free on Udacity with 325 seats available for interested applicants. Enrollments are open till 31st July 2020. Hence, all interested people should make it a point to apply before the deadline. This course will take you through the basics to the advanced level of machine learning using the AWS cloud platform. Students can also get cloud space and training worth $100 for free on the AWS cloud platform through the Github student developer pack.

AWS机器学习奖学金可在Udacity上免费获得,有325个席位可供感兴趣的申请人使用。 报名截止到2020年7月31日。因此,所有感兴趣的人都应在截止日期前提出申请。 本课程将带您学习使用AWS云平台进行机器学习的高级基础知识。 学生还可以通过Github学生开发人员包在AWS云平台上免费获得价值100美元的云空间和培训。

乌迪米 (Udemy)

Udemy is an amazing platform for learning all sorts of things. Out of the kind hearts of some Udemy instructors, they have made some of their top courses free to all during these hard times. Free courses from Udemy can be found here. Most of these courses are free for your lifetime and they require a simple sign-up for you to gain access.

Udemy是学习各种事物的绝佳平台。 在一些Udemy老师的帮助下,他们在困难时期向所有人免费提供了一些顶级课程。 Udemy的免费课程可以在这里找到。 这些课程大多数在您的一生中都是免费的,并且需要简单的注册才能获得访问权限。

很棒的学习 (Great Learning)

Great learning has a whole library of resources and tutorials for people at any level of experience in data science, AI, or ML. There are tutorials for mini projects and advanced level projects that you can try out to build a good data science, AI, or ML portfolio. It requires you to make a simple sign-up and you can access all those courses here. Courses taken from Great Learning are free for a lifetime.

出色的学习为数据科学,AI或ML领域的任何经验的人们提供了一个完整的资源库和教程。 有一些针对小型项目和高级项目的教程,您可以尝试构建良好的数据科学,AI或ML组合。 它要求您进行简单的注册,就可以在这里访问所有这些课程。 终身学习计划免费提供“伟大学习”课程。

升级 (upGrad)

19 top courses in tech have been made free on upGrad for a lifetime to anyone who registers. These courses come from a wide range of technologies but include beginner to advanced level courses in data science, artificial intelligence, and machine learning. The only thing required of you is a simple sign-up and viola!

在upGrad上 ,免费注册了19项顶尖的技术课程,终身免费。 这些课程来自多种技术,但包括数据科学,人工智能和机器学习的从入门到高级课程。 您唯一需要的就是简单的注册和中提琴!

教育性的 (Educative)

Educative is by far my favorite learning platform. With its engaging and smooth UI, you are guaranteed to have an amazing learning experience. The good news is that Educative has a Machine Learning Scholarship free and available to anyone interested in learning ML intensively for 3 months. This course normally costs $199 and is free now for every interested person. The only thing required of you is a sign-up and you are good to go.

到目前为止, 教育是我最喜欢的学习平台。 凭借其引人入胜且流畅的用户界面,可以确保您获得出色的学习体验。 好消息是,Educative拥有免费的机器学习奖学金 ,可供有兴趣在3个月内集中学习ML的任何人使用。 该课程通常收费199美元,现在对每个感兴趣的人免费。 您唯一需要做的就是注册,一切顺利。

openHPI (openHPI)

This a learning platform for Germans or people who can speak and understand German. openHPI has a free course on data science and data engineering. This course is taught in german and you receive a certificate upon completion. You can sign-up here.

这是德国人或会说和理解德语的人的学习平台。 openHPI提供有关数据科学和数据工程的免费课程。 本课程用德语授课,完成后您将获得证书。 您可以在这里注册。

SAS (SAS)

The leading name in analytics, SAS, is offering one-month long courses in data science, AI and machine learning, data curation, and advanced analytics. These normally cost $1295 per year each. A simple sign-up is all that is required of you to gain access to these courses from SAS.

SAS是分析学领域的佼佼者,它将提供为期一个月的数据科学,人工智能和机器学习,数据管理和高级分析课程。 这些通常每年花费$ 1295。 您只需进行简单的注册即可从SAS访问这些课程。

显然是AI (Obviously AI)

With a free account from Obviously AI, you will learn how to perform top-notch machine learning predictions and work with data without having to write any code. You also receive weekly emails from the team at Obviously AI with tips on how to use the platform and perform ML predictions with high accuracies. A free account will most likely be enough for individuals seeking to learn how to perform machine learning predictions using the no-code approach to data science, AI, and ML. However, as your needs increase, you can subscribe to any of the affordable paid plans to suit your needs.

借助来自Obviously AI的免费帐户,您将学习如何执行一流的机器学习预测以及如何处理数据而无需编写任何代码。 您还会收到来自Obviously AI团队的每周电子邮件,其中包含有关如何使用该平台以及以很高的准确性执行ML预测的提示。 对于想要学习如何使用针对数据科学,AI和ML的无代码方法来学习如何执行机器学习预测的个人而言,免费帐户很可能就足够了。 但是,随着需求的增长,您可以订阅任何可负担的有偿计划以适应您的需求。

Notitia AI (Notitia AI)

Notitia AI is the best virtual mentorship and training platform in the world today for aspiring data scientists and AI/ML engineers. Notitia AI takes applicants through a well-organized set of mentorship courses to make them industry ready for some of the top companies in the tech space. Notitia AI selects applicants twice a year for their cohorts and applicants will have to go through an interview session to be selected. Currently, there are no openings at Notitia AI since applicants for this season have just been selected. However, you can keep your eyes out on their social media platformsto know when the next cohort begins.

对于有抱负的数据科学家和AI / ML工程师, Notitia AI是当今世界上最好的虚拟指导和培训平台。 Notitia AI通过一组精心组织的指导课程为申请人提供指导,使他们为技术领域的一些顶级公司做好行业准备。 Notitia AI每年两次选择其队列的申请人,申请人必须经过面试才能被选中。 目前,Notitia AI尚未开放任何职位,因为刚刚选择了本赛季的申请人。 但是,您可以将注意力放在他们的社交媒体平台上,以了解下一个同类群组何时开始。

开源资源 (Open Source Resources)

One of the most important things about open source is that you get everything for free. You can check out this repository on GitHub for resources and a defined learning path to learning data science, AI, and ML. The courses and resources have been carefully curated to make sure you make the most out of learning while you own every bit of those resources for your lifetime. For a more challenging learning path, I recommend you commit to the #100DaysOfMLCode challenge where you get to learn almost everything from the basics of python to deep learning.

开源最重要的事情之一就是您免费获得所有内容。 您可以在GitHub上查看该存储库中的资源,以及定义的学习数据科学,AI和ML的学习路径。 这些课程和资源经过精心策划,以确保您一生中都充分利用这些资源,同时充分利用这些资源。 对于更具挑战性的学习途径,我建议您参加#100DaysOfMLCode挑战,您可以学习几乎所有内容,从python的基础知识到深度学习。

“Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.”― Richard Feynmann

“以最无拘无束,无礼和原始的方式努力学习最让您感兴趣的事物。”-理查德·费曼(Richard Feynmann)

大数据 机器学习 人工智能_在这个季节中,您如何免费学习数据科学,人工智能和机器学习。... (https://mushiming.com/)  第1张

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Some of the resources I shared in this article are available only for some time. I will make edits to this article on monthly basis and remove expired resources and add new ones. Please do try to check this article as often as you can to find new opportunities as they arrive.

我在本文中共享的一些资源仅在一段时间内可用。 我将每月对本文进行编辑,并删除过期的资源并添加新的资源。 请尽力检查这篇文章,以找到新的机会。

Thank you for making time to read this article. I hope you learned something and it has been helpful. You are welcome to share your thoughts, opinions, and links to resources I may have skipped in this article in the response section, and you can contact me directly on Twitter or LinkedIn. Happy hacking!

感谢您抽出时间阅读本文。 希望您学到了一些东西,对您有所帮助。 欢迎您分享您的想法,观点和指向资源的链接,我可能会在响应部分中跳过本文,也可以直接通过Twitter或LinkedIn与我联系。 骇客入侵!

A big thank you to Anna Ayiku for proofreading and correcting the many mistakes I made writing this.

非常感谢 Anna Ayiku 校对并纠正了我在撰写本文时犯下的许多错误。

翻译自: https://towardsdatascience.com/how-you-can-learn-data-science-ai-and-ml-for-free-during-this-season-820d9b0caf2d

大数据 机器学习 人工智能

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