自考数据结构和数据结构导论_我跳过大学自学数据科学

自考数据结构和数据结构导论

A few months back, I decided I wanted to learn data science. In order to do this, I skipped an entire semester of my data science major.

几个月前,我决定要学习数据科学。 为此, 我跳过了数据科学专业的整个学期。

背景 (Background)

When selecting a major, I wanted to pick a subject that guaranteed a job after graduation.

在选择专业时,我想选择一个可以保证毕业后能工作的学科。

It was around this time that data science started to become a hype. Harvard Business Review had just dubbed it as the “sexiest job of the 21st century.”

大约在这个时候,数据科学开始大肆宣传。 《哈佛商业评论》(Harvard Business Review)刚刚将其称为“ 21世纪最性感的工作”。

There were only one or two universities in the country offering a major in data science at that time, and I enrolled in one of them.

当时该国只有一两所大学提供数据科学专业,而我也参加了其中一所。

Just like everyone else pursuing the major, I was excited. I was going to learn the skills necessary to be at the forefront of a newly emerging technology!

就像其他人追求专业一样,我感到很兴奋。 我正要学习掌握最新技术所必需的技能!

Unfortunately, things didn’t exactly work out that way.

不幸的是,事情并没有完全按照这种方式解决。

一团糟 (It was a mess)

Image for post
Photo by Ricardo Viana on Unsplash
Ricardo Viana在Unsplash上拍摄的照片

Two years into the course, and I realized I wasn’t actually learning anything.

开学两年后,我意识到我实际上没有学到任何东西

Since we were the first batch of data science students, it seemed like the university’s data science faculty wasn’t properly set up yet.

由于我们是第一批数据科学专业的学生,​​因此好像大学的数据科学系尚未正确建立。

The lecturers had little to no knowledge on the subject, assignments were copy pasted from textbooks, and classes were not properly structured.

讲师对此主题知之甚少,甚至没有什么知识,作业是从教科书中复制粘贴的,并且课堂结构不正确。

As a result, none of us had a solid foundation in any aspect of data science.

结果,我们在数据科学的任何方面都没有扎实的基础。

Even after I finished an entire semester of machine learning (and getting an A in the class), I had little to no grasp on the topics taught.

即使我完成了一整个学期的机器学习(并在课程中获得A),我对所教授的主题也几乎一无所知。

An example of how poor our understanding of the subject was when my friend (also a straight A student) asked me what “supervised learning” meant after completing the entire semester.

一个例子是,当我的朋友(也是一个异性恋学生) 在完成整个学期后问我“监督学习”的含义时,我们对这个主题的理解却很差

After two years, I realized that I wasn’t going to have the skills I needed to add value to the job market, unless I did something. Fast.

两年后,我意识到,除非我有所作为,否则我将不会拥有为就业市场增值所需的技能。 快速。

创造自己的学习道路 (Creating my own learning path)

Image for post
Photo by Aaron Burden on Unsplash
照片由Aaron Burden在Unsplash上拍摄

I was going to university full time, and was involved in several club activities. I also tutored part time during the weekends.

我全职上大学,参与了一些俱乐部活动。 周末我还兼职辅导。

However, all this stopped a few months back when the government imposed a nationwide lockdown.

但是,几个月前政府实行全国封锁后,一切都停止了。

Suddenly, I had time on my hands. A lot of it.

突然间,我手上有了时间。 很多。

I decided to use this time to teach myself data science. I started out with little expectation, since I doubted my ability to pick up on the topics I needed to learn.

我决定利用这段时间自学数据科学。 一开始我的期望并不高,因为我怀疑自己是否有能力学习需要学习的主题。

I had little programming experience, and no understanding whatsoever of any data science topic.

我几乎没有编程经验,并且对任何数据科学主题都不了解。

I had to start from scratch.

我必须从头开始。

I started out with a course called “Python for Data Science and Machine Learning Bootcamp,” which taught me the very basics of data science in Python. This course sparked my interest in data science. The lecturer’s enthusiasm rubbed off on me.

我从一门名为“ Python for Data Science and Machine Learning Bootcamp ”的课程开始,该课程向我教会了Python数据科学的基础知识。 这门课程激发了我对数据科学的兴趣。 讲师的热情削弱了我。

For the first time in very long, I actually felt as though I was learning something.

很长时间以来,我第一次感到自己好像在学习一些东西。

I realized that it was possible for me to learn everything I had to know on my own, through the resources available online.

我意识到,通过在线资源,我可以自己学习所有必须了解的内容。

I spent around 7–8 hours watching online courses, reading, and doing projects. With trial and error, I created a learning path that worked for me.

我花了大约7-8个小时来观看在线课程,阅读和做项目。 经过反复试验,我创造了一条对我有用的学习道路 。

在获得学位课程的两年时间里,我在一个月内学到了更多。 (I learnt more in one month that I did in two years of my degree program.)

After a month, it was announced that we were to start online classes in university.

一个月后,宣布我们将在大学开始在线课程。

This took up a huge portion of my day, and I barely had time left to self-learn or do my own projects. Since the classes weren’t very helpful, I decided to skip them altogether.

这占了我一天的大部分时间,而我几乎没有时间去自学或做自己的项目。 由于课程的帮助不是很大,所以我决定完全跳过它们。

However, some of my lecturers are pretty strict about attendance.

但是,我的一些讲师对出勤非常严格。

One of them reported me for missing two week’s worth of classes, for which I produced a medical certificate.

其中一个报告说我错过了两周的课程,为此我出示了医疗证明。

I still didn’t think attending classes was worth my time, so I installed the Microsoft Teams app on my phone and joined class every day while I self-studied my own material.

我仍然认为上课不值得花我的时间,因此我在手机上安装了Microsoft Teams应用程序,每天都在自学材料的同时上课。

I would then stay up all night to complete my university assignments, mid-terms, and exams. Despite never going to class, I had no problem doing the coursework because I had already taught myself to do all those things.

然后,我会整夜熬夜以完成我的大学作业,期中考试和考试。 尽管从未上过课,但我毫无困难地完成课程工作,因为我已经教自己做所有这些事情。

I did this for a couple of months, and completed the entire semester without attending a single class.

我花了几个月的时间,完成了整个学期,没有上任何一堂课。

学习如何学习 (Learning how to learn)

Image for post
Photo by Matt Ragland on Unsplash
Matt Ragland在Unsplash上拍摄的照片

When self-studying, there are no exams to test you, no competition, and nobody to learn with.

自学时,没有考试可以考验您,没有竞争,也没有人可以学习。

This can make it difficult to stick it through, especially for those of us who are used to school and college environments.

这可能使其难以坚持下去,特别是对于那些习惯了学校和大学环境的人来说。

Most of us learn to pass exams, get good grades, and come out top in class. We thrive under these circumstances, because there are deadlines approaching and there is a need to study.

我们大多数人学会通过考试,获得良好的成绩并在课堂上名列前茅。 在这种情况下,我们会蓬勃发展,因为临近最后期限,需要学习。

自学教我如何学习。 (Self-studying taught me how to learn for the sake of learning.)

My learning was fuelled by curiosity, and nothing else.

好奇心推动了我的学习,仅此而已。

I’d spend hours staring in front of a computer screen trying to fix broken code. I would go to sleep at 9am in the morning after studying and completing college assignments.

我会花几个小时盯着电脑屏幕尝试修复损坏的代码。 学习并完成大学作业后,我将在早上9点入睡。

The only reason I could stick it through was because I was curious and hungry to learn more. I loved working on new projects, and learning to use new tools.

我坚持下去的唯一原因是因为我好奇并且渴望了解更多信息。 我喜欢从事新项目,也喜欢学习使用新工具。

I was inspired by senior data scientists who self-learnt and created their own learning path, and wanted to follow in the same footsteps. This motivation kept me going.

我受到了高级数据科学家的启发,他们自我学习并创建了自己的学习道路,并希望遵循同样的脚步。 这种动力使我继续前进。

结果 (The Results)

In just a few months of self-learning, I taught myself so much more than I ever imagined was possible.

在短短的几个月的自学过程中,我自学了很多东西,超出了我的想象。

I created a variety of data analysis projects, made tutorials for beginner data scientists, built my own portfolio website from scratch, and got a data science internship.

我创建了各种数据分析项目 , 为初级数据科学家制作了教程,从头开始构建了自己的投资组合网站 ,并获得了数据科学实习机会 。

These couple of months have opened up many new doors for me, and I finally feel like I am enjoying what I do.

这几个月为我打开了许多新的大门,我终于觉得自己很享受自己的工作。

Of course, there is so much I still don’t know, and there is a long way ahead. I am eager to learn new things as I go along.

当然,还有很多我仍然不知道,还有很长的路要走。 我渴望学习新事物。

That’s all for this article!

这就是本文的全部!

If you are looking to transition to data science or “break into the field,” just know that it is never too late to do so! You just need to have the discipline, and put aside some time everyday to learn new things.

如果您想过渡到数据科学或“涉足这一领域”,那就知道这样做永远不会太晚! 您只需要有纪律,每天就花些时间学习新事物。

翻译自: https://towardsdatascience.com/i-skipped-college-to-teach-myself-data-science-eb23fb6ed137

自考数据结构和数据结构导论

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处:http://www.mzph.cn/news/388953.shtml

如若内容造成侵权/违法违规/事实不符,请联系多彩编程网进行投诉反馈email:809451989@qq.com,一经查实,立即删除!

相关文章

十三、原生爬虫实战

一、简单实例 1、需求:爬取熊猫直播某类主播人气排行 2、了解网站结构 分类——英雄联盟——"观看人数" 3、找到有用的信息 二、整理爬虫常规思路 1、使用工具chrome——F12——element——箭头——定位目标元素 目标元素:主播名字&#xff0c…

归一化 均值归一化_归一化折现累积收益

归一化 均值归一化Do you remember the awkward moment when someone you had a good conversation with forgets your name? In this day and age we have a new standard, an expectation. And when the expectation is not met the feeling is not far off being asked “w…

sqlserver垮库查询_Oracle和SQLServer中实现跨库查询

一、在SQLServer中连接另一个SQLServer库数据在SQL中,要想在本地库中查询另一个数据库中的数据表时,可以创建一个链接服务器:EXEC master.dbo.sp_addlinkedserver server N别名, srvproductN库名,providerNSQLOLEDB, datasrcN服务器地址EXEC…

机器学习实践三---神经网络学习

Neural Networks 在这个练习中,将实现神经网络BP算法,练习的内容是手写数字识别。Visualizing the data 这次数据还是5000个样本,每个样本是一张20*20的灰度图片fig, ax_array plt.subplots(nrows10, ncols10, figsize(6, 4))for row in range(10):fo…

机器学习实践四--正则化线性回归 和 偏差vs方差

这次实践的前半部分是,用水库水位的变化,来预测大坝的出水量。 给数据集拟合一条直线,可能得到一个逻辑回归拟合,但它并不能很好地拟合数据,这是高偏差(high bias)的情况,也称为“欠…

深度学习 推理 训练_使用关系推理的自我监督学习进行训练而无需标记数据

深度学习 推理 训练背景与挑战📋 (Background and challenges 📋) In a modern deep learning algorithm, the dependence on manual annotation of unlabeled data is one of the major limitations. To train a good model, usually, we have to prepa…

CentOS 7 使用 ACL 设置文件权限

Linux 系统标准的 ugo/rwx 集合并不允许为不同的用户配置不同的权限,所以 ACL 便被引入了进来,为的是为文件和目录定义更加详细的访问权限,而不仅仅是这些特别指定的特定权限。 ACL 可以为每个用户,每个组或不在文件所属组中的用…

机器学习实践五---支持向量机(SVM)

之前已经学到了很多监督学习算法, 今天的监督学习算法是支持向量机,与逻辑回归和神经网络算法相比,它在学习复杂的非线性方程时提供了一种更为清晰,更强大的方式。 Support Vector Machines SVM hypothesis Example Dataset 1…

服务器安装mysql_阿里云服务器上安装MySQL

关闭防火墙和selinuxCentOS7以下:service iptables stopsetenforce 0CentOS7.xsystemctl stop firewalldsystemctl disable firewalldsystemctl status firewalldvi /etc/selinux/config把SELINUXenforcing 改成 SELINUXdisabled一、安装依赖库yum -y install make …

在PyTorch中转换数据

In continuation of my previous post ,we will keep on deep diving into basic fundamentals of PyTorch. In this post we will discuss about ways to transform data in PyTorch.延续我以前的 发布后 ,我们将继续深入研究PyTorch的基本原理。 在这篇文章中&a…

机器学习实践六---K-means聚类算法 和 主成分分析(PCA)

在这次练习中将实现K-means 聚类算法并应用它压缩图片,第二部分,将使用主成分分析算法去找到一个脸部图片的低维描述。 K-means Clustering Implementing K-means K-means算法是一种自动将相似的数据样本聚在一起的方法,K-means背后的直观是一个迭代过…

打包 压缩 命令tar zip

2019独角兽企业重金招聘Python工程师标准>>> 打包 压缩 命令tar zip tar语法 #压缩 tar -czvf ***.tar.gz tar -cjvf ***.tar.bz2 #解压缩 tar -xzvf ***.tar.gz tar -xjvf ***.tar.bz2 tar [主选项辅选项] 文件或目录 主选项是必须要有的,它告诉tar要做…

mysql免安装5.7.17_mysql免安装5.7.17数据库配置

首先要有 mysql-5.7.10-winx64环境: mysql-5.7.10-winx64 win10(64位)配置环境变量:1、把mysql-5.7.10-winx64放到D盘,进入D\mysql-5.7.10-winx64\bin目录,复制路径,配置环境变量,在path后面添加D\mysql-5.7.10-winx6…

tidb数据库_异构数据库复制到TiDB

tidb数据库This article is based on a talk given by Tianshuang Qin at TiDB DevCon 2020.本文基于Tianshuang Qin在 TiDB DevCon 2020 上的演讲 。 When we convert from a standalone system to a distributed one, one of the challenges is migrating the database. We’…

机器学习实践七----异常检测和推荐系统

Anomaly detection 异常检测是机器学习中比较常见的应用,它主要用于非监督学习问题,从某些角度看, 它又类似于一些监督学习问题。 什么是异常检测?来看几个例子: 例1. 假设是飞机引擎制造商, 要对引擎进行…

CODE[VS] 1621 混合牛奶 USACO

题目描述 Description牛奶包装是一个如此低利润的生意,所以尽可能低的控制初级产品(牛奶)的价格变的十分重要.请帮助快乐的牛奶制造者(Merry Milk Makers)以可能的最廉价的方式取得他们所需的牛奶.快乐的牛奶制造公司从一些农民那购买牛奶,每个农民卖给牛奶制造公司的价格不一定…

刚认识女孩说不要浪费时间_不要浪费时间寻找学习数据科学的最佳方法

刚认识女孩说不要浪费时间重点 (Top highlight)Data science train is moving, at a constantly accelerating speed, and increasing its length by adding up new coaches. Businesses want to be on the data science train to keep up with the ever-evolving technology a…

测试工具之badboy

badboy这个工具本身用处不是很大,但有个录制脚本的功能,还是jmeter脚本,所以针对这一点很多懒人就可以通过这个录制脚本,而不需要自己去编写 badboy工具最近还是2016年更新的,后面也没在更新了,官方下载地址…

hive 集成sentry

2019独角兽企业重金招聘Python工程师标准>>> 环境 apache-hive-2.3.3-bin apache-sentry-2.1.0-bin 1 2 sentry是目前最新的版本,支持hive的最高版本为2.3.3,hive版本如果高于2.3.3,会出一些版本兼容问题[亲测] hive快速安装 wget…

isql 测试mysql连接_[libco] 协程库学习,测试连接 mysql

历史原因,一直使用 libev 作为服务底层;异步框架虽然性能比较高,但新人学习和使用门槛非常高,而且串行的逻辑被打散为状态机,这也会严重影响生产效率。用同步方式实现异步功能,既保证了异步性能优势&#x…