数据科学与大数据排名思考题_排名前5位的数据科学课程
數據科學與大數據排名思考題
目錄 (Table of Contents)
介紹 (Introduction)
For this article, I will focus on the top Data Science courses on Udemy, decided by Udemy [2]. In the past, I have looked into Kaggle, another prominent platform that shared knowledge on all things Data Science. I wanted to branch out and include courses on a platform where nearly 4 million students are learning Data Science. The top courses are also known as the most popular on Udemy; there are also the highest-rated and newest. I wanted to first talk about other platforms that were free, so I do have an article on those topics, which I will include at the end of this article. For now, these Udemy courses all cost around $100. I will outline the main features of each of the top five data science courses on Udemy below.
對于本文，我將重點介紹由Udemy [2]決定的有關Udemy的頂級數據科學課程。 過去，我研究過Kaggle，它是另一個著名的平臺，可共享有關數據科學的所有知識。 我想擴展到一個平臺上，并在將近400萬學生學習數據科學的平臺上開設課程。 熱門課程也被稱為Udemy上最受歡迎的課程； 也有收視率最高和最新的 。 我想先談談其他免費的平臺，所以我確實有一篇關于這些主題的文章，我將在本文結尾處發表。 目前，這些Udemy課程的總費用約為100美元。 我將在下面概述有關Udemy的前五項數據科學課程的主要功能。
Included in each course section in this article will be what is included, some useful facts about the course, and what is unique about the course — what separates them from the other respective courses on Udemy.
本文的每個課程部分將包括其中的內容，有關該課程的一些有用事實以及該課程的獨特之處-將它們與有關Udemy的其他各個課程區分開來。
烏迪米 (Udemy)
As mentioned earlier, nearly 4 million students are on Udemy for just Data Science alone, so you can validate that these course information, reviews, and benefits are up to a high standard. I wanted to attest that the knowledge in these courses is something worthy of your investment, as I am a Senior Data Scientist who has primarily learned online from courses like these.
如前所述，僅數據科學領域的Udemy學生就有近400萬，因此您可以驗證這些課程信息，評論和收益是否達到了高標準。 我想證明這些課程中的知識值得您投資，因為我是一位高級數據科學家，主要從此類課程中在線學習。
I would like to include more courses from other platforms, but for this article, the focus will be on Udemy. Feel free to comment down below any platforms or websites you would like to see me write about.
我想包括其他平臺的更多課程，但對于本文，重點將放在Udemy上。 請隨意在您希望看到我寫信的任何平臺或網站下方進行評論。
機器學習AZ?：數據科學中的動手Python和R (Machine Learning A-Z?: Hands-On Python & R In Data Science)
Our top course includes all things Machine Learning with not only Python programming language practice, but R as well. There are 10 main parts included in this course, all including very valuable key concepts of Data Science. At this moment, the course has a 4.5-star rating out of 5 stars with nearly 130,000 ratings, costing $104.99 [3].
我們的頂級課程包括機器學習所有內容，不僅包括Python編程語言實踐，還包括R。 本課程包括10個主要部分，全部包括非常有價值的數據科學關鍵概念。 目前，該課程在5顆星中獲得4.5顆星的評分，其中近130,000顆星的評分為$ 104.99 [3]。
包含什么？ (What is included?)
You can expect to learn a myriad of skills and concepts like:
您可以期望學習各種技能和概念，例如：
- Python and R Python和R
- Accurate predictions 準確的預測
- Robust Machine Learning models 強大的機器學習模型
- Dimensionality Reduction 降維
- Intuition 直覺
- Powerful analysis 強大的分析
- Added value for your business 為您的業務增值
- Reinforcement learning, NLP, and Deep Learning 強化學習，NLP和深度學習
- Knowing which Machine Learning model is for each problem 知道哪種機器學習模型適合每個問題
Some other important stats to know are that there are:
需要了解的其他一些重要統計數據包括：
45 sections323 lectures44h 30m total lengthTo set these popular courses apart, I will also be outlining unique features about the courses, as most of them are all-inclusive in Data Science.
為了使這些熱門課程與眾不同，我還將概述這些課程的獨特功能，因為其中大多數都包含在數據科學中。
有什么獨特之處？ (What is unique?)
- Apriori associate rule learning — in both Python and R Apriori關聯規則學習-在Python和R中
- Eclat associate rule learning — in both Python and R eclat關聯規則學習-在Python和R中
It is recommended that you have some basic mathematics knowledge at the high school level. Most people who use this course are interested in Machine Learning, who are not as comfortable with coding, and want to start a career in Data Science. You can, of course, also utilize this course to brush up and improve upon your current kills, as well as making your resume more competitive.
建議您在高中階段具備一些基本的數學知識。 使用本課程的大多數人都對機器學習感興趣，他們對編碼不太滿意，并希望開始從事數據科學職業。 當然，您也可以利用此課程來完善和改進當前的技能，以及使簡歷更具競爭力。
適用于數據科學和機器學習訓練營的Python (Python for Data Science and Machine Learning Bootcamp)
This course focuses on Python for both Data Science and Machine Learning; including NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, TensorFlow, and more. This $109.99 course’s rating is slightly higher at 4.6 stars, but with fewer ratings around 83,000 [4].
本課程的重點是用于數據科學和機器學習的Python； 包括NumPy，Pandas，Seaborn，Matplotlib，Plotly，Scikit-Learn，機器學習，TensorFlow等。 這門$ 109.99的課程評分稍高一點，為4.6星，但評分較少，大約為83,000 [4]。
包含什么？ (What is included?)
There are quite a few things this course highlights that you will learn, including, but not limited to:
本課程將重點介紹許多要學習的內容，包括但不限于：
- Pandas for Data Science 熊貓數據科學
- Seaborn for statistical plots Seaborn統計圖
- SciKit-Learn for Machine Learning SciKit-學習機器學習
- Logistic Regression 邏輯回歸
- Random Forest and Decision Trees 隨機森林和決策樹
- Neural Networks 神經網絡
- Matplotlib and Plotly for plotting and dynamic visualizations Matplotlib和Plotly用于繪圖和動態可視化
Some other important stats to know are that there are:
需要了解的其他一些重要統計數據包括：
27 parts165 lectures24h 54m total lengthTo set this course apart from the others, I will include some unique sections this course offers.
為了使本課程與眾不同，我將提供本課程提供的一些獨特部分。
有什么獨特之處？ (What is unique?)
Spark for Big Data Analysis — this skill is extremely useful and lucrative
大數據分析的火花- 此技能非常有用且有利可圖
- Natural Langauge Processing and Spam Filters 天然語言處理和垃圾郵件過濾器
I really like that these unique factors are included in this course as I have seen most data scientists fail to have Spark experience, and somewhat have Natural Language Processing (NLP), but usually without useful, practical implication knowledge.
我真的很喜歡將這些獨特的因素包括在本課程中，因為我已經看到大多數數據科學家都沒有Spark經驗，并且有些人具有自然語言處理(NLP)，但通常沒有有用的，實際的暗示知識。
2020年數據科學課程：完整的數據科學訓練營 (The Data Science Course 2020: Complete Data Science Bootcamp)
This course especially prides itself in the year 2020, so you can rest assured it is up-to-date. This course focuses on mathematics, statistics, Python, advanced statistics in Python, and Machine and Deep Learning. With a rating of 4.5 stars and around 72,000 ratings, this $114.99 course is the third most popular course on Udemy for Data Science [5].
該課程在2020年尤其引以為傲，因此您可以放心，它是最新的。 本課程側重于數學，統計學，Python，Python中的高級統計學以及機器和深度學習。 這項價格為$ 114.99的課程獲得了4.5星的好評，并且獲得了72,000個評分，它是Udemy for Data Science上第三受歡迎的課程[5]。
包含什么？ (What is included?)
There are even more concepts in this course that are highlighted than the previous course. You will learn, including, but not limited to:
與上一課程相比，本課程中強調的概念更多。 您將學習，包括但不限于：
- Underfitting, overfitting, training, validation, and n-fold cross-validation 擬合不足，擬合過度，訓練，驗證和n折交叉驗證
- Testing, hyperparameters 測試，超參數
- Pre-process data 預處理數據
- Cluster and factor analysis 聚類和因子分析
- Deep neural networks 深度神經網絡
Some other important stats to know are that there are:
需要了解的其他一些重要統計數據包括：
62 sections471 lectures28h 52m total lengthTo set this course apart from the others, I will include some unique sections this course offers.
為了使本課程與眾不同，我將提供本課程提供的一些獨特部分。
有什么獨特之處？ (What is unique?)
- Tableau 畫面
- Google’s TensorFlowDevelop 谷歌的TensorFlowDevelop
Tableau is something you may not learn in other courses or at a university, so this course will offer some additional benefits with this unique skill. The TensorFlowDevelop by Google is also unique and offers a way to code and solve important business problems with big data.
Tableau是您在其他課程或大學中可能不會學到的東西，因此，使用此獨特技能，本課程將提供一些其他好處。 Google的TensorFlowDevelop也是獨特的，它提供了一種編碼和解決大數據重要業務問題的方法。
R編程AZ?：R結合實際練習，用于數據科學！ (R Programming A-Z?: R For Data Science With Real Exercises!)
Whereas most of the previous courses focused on Python, this course focuses on R. You can expect to learn R Studio, Data Analytics, Data Science, functions, and ggplot2. With a rating of 4.6 stars from about 34,000 students, this course is cheaper at $94.99 [6].
之前的大多數課程都針對Python，而本課程則針對R。您可以期望學習R Studio，數據分析，數據科學，函數和ggplot2。 大約34,000名學生獲得4.6星的評價，這門課程的價格較為便宜，為$ 94.99 [6]。
包含什么？ (What is included?)
There are several concepts in R that you will learn in this course, including, but not limited to:
您將在本課程中學習R中的幾個概念，包括但不限于：
- Core principles of R programming R編程的核心原理
- Creating variables 創建變量
- while() and for() loop in R R中的while()和for()循環
- matrix(), rbind(), and cbind() functions matrix()，rbind()和cbind()函數
- Understanding the Normal distribution 了解正態分布
- Creating vectors in R 在R中創建向量
- Practice with statistical data in R 在R中使用統計數據進行練習
Some other important facts to know is that there are:
要知道的其他一些重要事實是：
8 sections82 lectures10h 39m total length有什么獨特之處？ (What is unique?)
- Working with financial data 處理財務數據
- Law of Large Numbers 大數定律
Apart from this course being completely over R programming, this course offers unique concepts that are very beneficial as well. As a Data Scientist who has worked with tons of financial data, I can attest to how useful and practical it is to study with financial data in not only Python, but R as well. This course also seems to focus more on statistics with the inclusion of the Law of Large Numbers, which is something I did not find as prominent in the other courses.
除了完全通過R編程來學習本課程之外，本課程還提供了非常有益的獨特概念。 作為處理大量財務數據的數據科學家，我可以證明，不僅使用Python而且使用R對財務數據進行研究是多么有用和實用。 本課程似乎也將重點放在統計學上，包括《大數定律》，這是我在其他課程中沒有發現的。
數據科學AZ?：包括現實生活中的數據科學練習 (Data Science A-Z?: Real-Life Data Science Exercises Included)
Last but not least, this course focuses on everything Data Science with the importance of exercises. You can expect to learn real Analytics examples, Data Mining, Model, and Tableau visualizations. Also cheaper, this course is $94.99, with a 4.6 rating from around 27,000 raters [7].
最后但并非最不重要的一點是，本課程側重于所有具有練習重要性的數據科學。 您可以期望學習真正的Analytics示例，數據挖掘，模型和Tableau可視化。 同樣便宜的是，這門課程的價格為94.99美元，來自27,000個評估者提供4.6評分[7]。
包含什么？ (What is included?)
Out of all of the courses, this course lists the most concepts. You will learn, including, but not limited to:
在所有課程中，本課程列出了最多的概念。 您將學習，包括但不限于：
- Data Mining in Tableau Tableau中的數據挖掘
- Ordinary Least Squares for creating Linear Regressions 用于創建線性回歸的普通最小二乘法
- Reading a confusion matrix 讀取混亂矩陣
- Training and test data for robust model building 訓練和測試數據以建立可靠的模型
- Cleaning data and anomaly detection 清潔數據和異常檢測
- Chi-Sqaured staatsical test 卡方統計檢驗
Some other important facts to know is that there are:
要知道的其他一些重要事實是：
28 sections217 lectures21h 18m total lengthThis course, perhaps, offers the most unique concepts and skills that you can learn in Data Science. It not only references statistics in-depth , but SQL as well.
本課程也許提供您可以在數據科學中學習的最獨特的概念和技能。 它不僅引用了深入的統計信息，而且還引用了SQL。
有什么獨特之處？ (What is unique?)
- Understanding the Odds Ratio 了解賠率
- Create Scripts in SQL 在SQL中創建腳本
- Robust Geodemographic Segmentation Model 魯棒的地理人口分割模型
- Building a CAP curve in Excel 在Excel中建立CAP曲線
摘要 (Summary)
Photo by Jude Beck on Unsplash [8]. 裘德·貝克 ( Jude Beck)在《 Unsplash 》上的照片 [8]。To be quite frank, although these courses are on the pricey side, or simply not free, they are still, by far, a great deal. You will have hours upon hours, hundreds of lectures, and a plethora of common and unique data science sections. You have now learned some of the overviews of the top five Data Science courses on Udemy. Here they are again, listed out for easy viewing:
坦率地說，盡管這些課程價格昂貴，或者根本不是免費的，但到目前為止，它們仍然是很多。 您將要花費數小時的時間，數百次講座，以及大量常見和獨特的數據科學部分。 您現在已經了解了有關Udemy的前五門數據科學課程的一些概述。 在此再次列出，以方便查看：
Machine Learning A-Z?: Hands-On Python & R In Data SciencePython for Data Science and Machine Learning BootcampThe Data Science Course 2020: Complete Data Science BootcampR Programming A-Z?: R For Data Science With Real Exercises!Data Science A-Z?: Real-Life Data Science Exercises IncludedThank you for reading my article. I hope you found it both interesting and useful. Please feel free to comment down below and suggest some other common or unique courses you can take on Udemy.
感謝您閱讀我的文章。 我希望您發現它既有趣又有用。 請在下面隨意評論，并建議您可以選擇參加Udemy的其他一些常見或獨特的課程。
Here are the links to my other articles regarding Data Science courses on both Kaggle [8]:
這是我在Kaggle [8]上有關數據科學課程的其他文章的鏈接：
I am not affiliated with Udemy. I am reporting the most popular Data Science courses on their website, as well as my commentary and view of them and what makes them unique.
我不隸屬于Udemy。 我在他們的網站上報告了最受歡迎的數據科學課程，以及我對它們的評論和看法以及使它們與眾不同的原因。
翻譯自: https://towardsdatascience.com/the-top-5-data-science-courses-4edf005ceaa5
數據科學與大數據排名思考題
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