README Data-Analysis-With-Python Using Python, pandas and numpy to analyze data in a Coursera course. Lessons covered in this course Loading, Querying, and Filtering Data (csv) Loading, Querying and Filtering Data (pandas) Summarizing and Visualizing Data (pandas, numpy)About...
pythondata-sciencecourseraprojectpython3data-analysisibmjupyter-notebookspython-for-data-analysiswatson-studioibm-data-science-professional UpdatedJul 4, 2020 Jupyter Notebook This project is part of a university course designed to integrate machine learning techniques into the domain of computer networks. ...
Python部分难度远不如Coursera上University of Michigan的Applied Data Science with Python专项课,SQL部分也不如Duke University的那门Managing Big Data with MySQL。九门课都通过以后,你会得到一张title很牛逼的证书,IBM数据科学专业证书... 不过说实话,这门课也就是个普通数据分析师的水准,远不及数据科学家......
Data Science Toolbox Coursera Course Data Science Toolbox Blog Wolfram Data Science Platform Take numerical, textual, image, GIS or other data and give it the Wolfram treatment, carrying out a full spectrum of data science analysis and visualization and automatically generate rich interactive reports...
courses on Coursera with a rating of 4.9 out of 5. The courses provide an introduction to algorithms and data structures with emphasis on applications and scientific performance analysis of Java implementations. Though the concepts are language independent, the solutions and implementations are done in...
Inferential analysis: Makes predictions about larger populations from sample data Exploratory Data Analysis (EDA): Explores data with an open mind, absent of preconceived ideas Diagnostic analysis: Like a doctor looking for a possible cause of illness, this technique investigates cause-and-effect relati...
There are 10 courses in this certification program with a Capstone project at the end. These courses cover tools that data analysts and data scientists work with like version control, markdown, git, GitHub, and RStudio, R Programming, Getting and Cleaning Data, Exploratory Data Analysis technique...
Technology can change fast—which means you must be aware of the newest big data tools (such as AI for data analysis) and understand how to use them to make your current systems better. Of course, you don’t need to go at it alone to keep up with these changes— a large data ...
and libraries, Python, databases, SQL, data visualisation, data analysis, statistical analysis, predictive modelling, and machine learning techniques, among other things. Using actual data science tools and real-world data sets, you’ll study data science through hands-on experience on the IBM ...
About Happy Git and GitHub for the useR PDF:The target reader is someone who uses R for data analysis or who works on R packages, although some of the content may be useful to those working in adjacent areas.Open Free BookAgile Data Science with R: A workflow...