When I completed the Springboard Data Science Career Track curriculum earlier this year, multiple people have reached out to me wanting to know more about the program, curriculum and my experience with it. This post is a review of my experiences with the Springboard Data Science Curriculum, based on my personal experience. For a TL; DR version, feel free to jump to the pro’s and con’s listed at the end.

当我在今年早些时候完成Springboard数据科学职业跟踪课程时，有很多人向我伸出援手，想进一步了解该程序，课程和我的经验。 这篇文章根据我的个人经历，回顾了我在Springboard数据科学课程中的经历。 对于TL； DR版本，可以随意跳到结尾处的专业人士和反对者名单。

These days, there are several options, both free and paid, available online for working professionals who want to make a career transition toward data science or just want to develop an additional skill set. I am hoping that this article will help those considering enrolling in a formal data science curriculum to get an overview of what they can expect from Springboard program. This should help those considering a formal program to better compare Springboard to other programs and make an informed decision about whether it aligns with their learning goals. Note that this review is based on my personal experience with “ Springboard Data Science Career Track” program which I took during late 2019/ early 2020.

如今，有几种免费和付费的选择，可供希望在数据科学领域转向职业或仅想开发其他技能的职业专业人员在线使用。 我希望本文将对那些考虑参加正规数据科学课程的人有所帮助，以概述他们对Springboard计划的期望。 这应该帮助那些正在考虑正式计划的人更好地将Springboard与其他计划进行比较，并就是否符合他们的学习目标做出明智的决定。 请注意，此评论是基于我在2019年末/ 2020年初参加的``Springboard Data Science Career Track''计划的个人经验。

Before diving into the course overview, I will start off with a little background about me and my motivation for enrolling in the program. Hopefully, this puts my observations in perspective. When I enrolled in the program, I have a PhD in Mechanical Engineering and was working as a process engineer in semiconductor manufacturing for around two years. At this point, I completed a few projects which introduced me to machine learning and made me realize the vast potential for AI based improvements in manufacturing. So, I decided develop my data science skill set and get more exposure to the field. I chose Springboard because it is more rigorous and holistic than completing various MOOC’s or learning from tutorials online while not as big of a commitment as a full time degree (and less expensive, too), Furthermore, I was able to complete it at my own pace while working full time. With this context, lets get into the overview of the program

在深入学习课程概述之前，我将首先介绍一些有关我的背景以及我参加该计划的动机。 希望这能使我的观察成为现实。 当我注册该计划时，我获得了机械工程博士学位，并在半导体制造领域担任过程工程师大约两年了。 至此，我完成了一些项目，将我介绍给机器学习，使我意识到基于AI的制造改进的巨大潜力。 因此，我决定发展自己的数据科学技能并进一步接触该领域。 我之所以选择Springboard，是因为它比完成各种MOOC或在线学习教程更严格，更全面，而且不像全日制学位那样投入大量资金(而且费用也不高)，而且，我能够自己完成它全职工作时保持节奏。 在这种情况下，让我们进入程序概述

计划概述 (Program Overview)

The first thing that happens once you enroll in the program is that you will be given access to the program curriculum in your Springboard account. You can access the initial learning modules (except those that belong to the Specialization) right from the beginning. You will also be able to access the course tracker and other useful information like community forums, mentor call notifications and other student resources. The program has multiple resources and tools available to help you make the most out of it.

一旦注册该计划，第一件事就是您将获得在Springboard帐户中访问该计划课程的权限。 您可以从一开始就访问初始学习模块(属于专业的模块除外)。 您还可以访问课程跟踪器和其他有用的信息，例如社区论坛，指导电话通知和其他学生资源。 该程序具有多种资源和工具，可帮助您最大程度地利用它。

Throughout the program, the curriculum is designed to ensure that you are making progress on technical modules, career development modules and capstone projects simultaneously. Finally, one-on-one mentor support is one of the strongest selling points for springboard. Let’s go over each of these separately next.

在整个计划中，该课程旨在确保您在技术模块，职业发展模块和顶峰项目上同时取得进展。 最后，一对一的导师支持是跳板的最大卖点之一。 接下来让我们分别讨论每个。

Technical Curriculum Modules

技术课程模块

For technical curriculum, springboard does not develop its own material but organizes and provides access to other resources on the web, both free and paid. I felt the units to be logically organized and material to be well curated. Material start off with basic data science skills including data parsing, data manipulations, visualization and basic statistics before moving on to different machine learning topics.

对于技术课程，Springboard不会自行开发资料，而是组织并提供对Web上其他免费和付费资源的访问。 我觉得各个单元要合理地组织起来，素材要精心策划。 在开始学习不同的机器学习主题之前，材料首先要具备基本的数据科学技能，包括数据解析，数据处理，可视化和基本统计​​信息。

I found that the material on machine learning gives a good overview of different types of models and helps build an intuitive understanding of how the model works. In general, the material seems to be aimed at introducing the various models, developing an intuition about how they work and making you use the model libraries in python. However, if you are looking for in-depth mathematical theory or implementation details about specific algorithms, you may not find that in the curriculum.

我发现有关机器学习的材料很好地概述了不同类型的模型，并有助于建立对模型工作方式的直观了解。 一般而言，该材料似乎旨在介绍各种模型，对它们的工作方式产生直觉，并让您使用python中的模型库。 但是，如果您正在寻找有关特定算法的深入数学理论或实现细节，则可能在课程中找不到。

Being a career track program, the curriculum does a good job of covering additional skills required for data scientists by including modules on good coding practices, testing and debugging your code as well as productionizing data science models.

作为职业跟踪计划，该课程很好地涵盖了数据科学家所需的其他技能，方法是包括有关良好编码实践的模块，测试和调试代码以及​​生产数据科学模型的模块。

Finally, the program gives an option to choose between three specializations, each of which will have different modules for about the last 30% of the course. The specializations available are for Data Science Generalist, Deep Learning and Natural Language Processing. I chose NLP as my specialization and did not look at the quality of the material in other specializations first hand. However, based on talking to other students, I understand generalist track covers models like recommendation systems in more detail. My observations are based on NLP specialization I chose.

最后，该程序提供了一个选项，供您选择三个专业，每个专业在课程的最后30％左右都有不同的模块。 可用的专业是数据科学通才，深度学习和自然语言处理。 我选择NLP作为我的专业，但没有直接了解其他专业的材料质量。 但是，基于与其他学生的交谈，我更全面地了解了通识教育课程涵盖的模型，例如推荐系统。 我的观察基于我选择的NLP专业化。

Capstone Projects

顶峰项目

I found the capstone projects to be very helpful to apply the skills I learn as a part of the technical curriculum. These are a good opportunity to develop a data science portfolio, which can be very helpful during job search, especially if you are planning to transition to data science jobs from a different field.

我发现顶峰项目对于将我学到的技能应用到技术课程中非常有用。 这是开发数据科学产品组合的好机会，这在求职过程中可能会非常有帮助，特别是如果您打算从不同的领域过渡到数据科学工作。

You are expected to select the first Capstone project early on and make progress on the projects alongside the technical curriculum. In addition to the code, you will also be required to document your findings as a report and a presentation as a part of final submission.

您应尽早选择第一个Capstone项目，并与技术课程一起在这些项目上取得进展。 除代码外，还要求您将调查结果记录为报告，并作为最终提交的一部分进行演示。

If you are interested in applying data science to a particular domain, projects will let you pick a dataset from the same domain so you can get familiar with the data and common strategies for data wrangling and feature selection in that domain.

如果您有兴趣将数据科学应用于特定领域，则可以使用项目从同一领域中选择数据集，以便熟悉该领域的数据以及数据整理和特征选择的通用策略。

Mentor Support

导师支持

One of the main selling points of Springboard is their one-on-one mentoring. When you enroll in the program, Springboard will pair you with a mentor based on your preferences and what you are looking for in the course. You will have regular 30-minute check-ins with the mentor for the duration of the course. Mentor is your main resource for keeping track of your progress, getting help understanding topics if you get stuck and for grading and providing feedback on your assignments and capstone projects.

Springboard的主要卖点之一是一对一的辅导。 当您注册该计划时，Springboard将根据您的偏好和您在课程中寻找的内容与导师配对。 在整个课程期间，您将定期与导师进行30分钟的签到。 Mentor是您的主要资源，可用于跟踪进度，在遇到困难时帮助您理解主题以及为作业评分和提供顶峰项目反馈。

Based on mentor profiles on the Springboard website, I found that the mentors can have varying backgrounds, including those with advanced degrees in data science related fields as well as those with non-STEM backgrounds who successfully transitioned to data science. I suggest that you think about your career goals and what you are expecting to get out of your mentor before giving your mentor preferences. Technically, you do not get to select your mentor directly. Instead, Springboard assigns you a mentor based on your preferences and availability. However, I found the Springboard team to be helpful in trying to understand my preferences and changing the assigned mentor early on in the program.

根据Springboard网站上的导师简介，我发现导师的背景各不相同，包括具有数据科学相关领域的高级学位的人员以及成功过渡到数据科学的具有非STEM背景的人员。 我建议您在给出导师偏好之前，先考虑自己的职业目标以及期望从导师那里得到的收获。 从技术上讲，您不会直接选择导师。 相反，Springboard会根据您的偏好和可用性为您分配一名导师。 但是，我发现Springboard团队在尝试了解我的偏好并在程序的早期更改分配的指导者方面会有所帮助。

In addition to the assigned mentor, you will also get unlimited one off mentor calls. I found these to be helpful if you need someone else to give you a different perspective on a topic or if you find yourself stuck midway during the week and don’t want to wait till the next scheduled mentor call to get unblocked.

除了分配的导师，您还将获得无限制的一次导师电话。 如果您需要其他人就某个主题提供不同的观点，或者您发现自己在一周中途陷入困境，并且不想等到下一个预定的导师电话来畅通无阻，我会发现这些方法很有帮助。

Career Development Module and Career Coaching Calls

职业发展模块和职业指导电话

The program has career development curriculum modules interspersed between technical modules and you are expected to work on them simultaneously. Material included is related to common career development topics like updating Linkedin profile, resume writing and informational interviews. As a significant part of job search is networking, you will be encouraged to develop your network through informational interviews, participating in meet-up’s and reaching out to other contacts in your chosen company or job profile.

该计划的职业发展课程模块插在技术模块之间，您应该同时进行研究。 包含的材料与常见的职业发展主题相关，例如更新Linkedin资料，简历撰写和信息采访。 联网是求职的重要组成部分，因此，我们鼓励您通过信息面试，参加聚会以及与所选公司或职位资料中的其他联系人联系来发展您的网络。

You will also be scheduling calls with one of the career coaches who can review your job search materials and strategy to give personalized feedback. As a part of the program, you will have access to career coaching and can schedule mock interviews up to six months after the end of your program, as long as you are actively searching for jobs.

您还将安排一位职业教练安排电话，他们可以查看您的求职材料和策略以提供个性化反馈。 作为该计划的一部分，只要您正在积极寻找工作，就可以在职业生涯结束后的六个月内安排模拟面试，并且可以安排模拟面试。

Other Tools and Resources

其他工具和资源

In addition to those mentioned before, you can also attend weekly office hours to watch Capstone project presentations by other students or ask general questions. You will also have access to discussion forums or participate in peer study groups, which are a good resource for networking with other students and brainstorming project ideas. They also conduct Springboard Rise, an in-person conference/ networking event in SFO bay area.

除了前面提到的内容外，您还可以参加每周的办公时间，观看其他学生的Capstone项目演示或提出一般性问题。 您还将可以访问讨论论坛或参加同行学习小组，这是与其他学生建立联系并集思广益项目想法的良好资源。 他们还在SFO海湾地区进行现场会议/社交活动Springboard Rise。

Finally, to summarize, Springboard offers a holistic and well-curated program for anyone wanting to develop their data science skill set and pivot to a data science career. You can take advantage of multiple resources for professional development and networking while developing your technical skills and creating a project portfolio. However, the expected time commitment is obviously higher than a typical MOOC and you need to pass an initial skills assessment to be admitted to the program.

最后，总而言之，Springboard为想要发展其数据科学技能并转向数据科学职业的任何人提供了一个完整且精心策划的程序。 您可以利用多种资源进行专业开发和联网，同时发展自己的技术技能并创建项目组合。 但是，预期的时间投入明显高于典型的MOOC，您需要通过初步技能评估才能被录取。

利弊 (Pros and Cons)

Pros

优点

1. Curriculum is broader and holistic compared to a MOOC class. So, likely more credible, especially for those for whom going back to school is not an option与MOOC课程相比，课程更广泛，更全面。 因此，可能更可信，尤其是对于那些无法重返校园的人而言
2. The course has opportunities to participate in discussion forums, peer study groups and attend in-person networking events, which are useful to learn more about the data science community and network with other peers who may be trying to get into the field as well本课程有机会参加讨论论坛，同行研究小组并参加面对面的社交活动，这对于了解有关数据科学社区的更多信息以及与可能也尝试进入该领域的其他同行的交流非常有用
3. The curriculum is curated and organized logically. Very good for those starting out in the field and trying to quickly develop a foundation an all aspects of data science该课程是按逻辑安排和组织的。 对于刚开始该领域并试图快速建立数据科学各个方面的基础的人员来说非常好
4. You will have accountability. There is a tracker as well as weekly check-ins with mentor. This will make it easier to work stay consistent through periods of low motivation您将承担责任。 有一个跟踪器，以及每周有导师陪同的入住手续。 这将使在低动力时期保持一致的工作变得更加容易
5. Ability to pick a specialization. For the final few modules, you will be able to specialize in one of three tracks based on interests and career goals : Natural Language Processing, Deep Learning and Generalist Machine Learning能够选择专业。 对于最后的几个模块，您将能够基于兴趣和职业目标来专注于以下三个领域之一：自然语言处理，深度学习和通用机器学习

Cons

缺点

1. Pricey. While its true you are getting many resources for the price, if you are unlikely to use everything, there may be better options available贵 确实，您可以获得很多资源，但如果您不太可能使用所有内容，那么可能会有更好的选择
2. Course is developed primarily using Python and its libraries. If you prefer or looking to learn R or other programming language, this may not be for you课程主要是使用Python及其库开发的。 如果您喜欢或希望学习R或其他编程语言，可能不适合您
3. Experience with mentor can vary. The mentors listed on website have a broad range of backgrounds, from PhD’s in machine learning based disciplines to non-STEM majors who transitioned to Data Science. Make sure to let the Springboard team aware of your preference and what you are looking for so you can be matched with someone who can help you best导师的经验会有所不同。 网站上列出的导师背景广泛，从基于机器学习的博士学位到过渡到数据科学的非STEM专业人士。 确保让Springboard团队了解您的喜好和所要寻找的东西，以便与可以为您提供最佳帮助的人相匹配