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    47 courses found for data analysis
    • Data Analysis with Python and Pandas
      Self-paced - Intermediate
      About this course:|Python programmers are some of the most sought-after employees in the tech world, and Python itself is fast becoming one of the most popular programming languages. One of the best applications of Python however is data analysis; which also happens to be something that employers can't get enough of. Gaining skills in one or the other is a guaranteed way to boost your employability - but put the two together and you'll be unstoppable!|Learn efficient python data analysis|Manipulate data sets quickly and easily|Master python data mining|Gain a skillset in Python that can be used for various other applications|This course contains 51 lectures and 6 hours of content, specially created for those with an interest in data analysis, programming, or the Python programming language. Once you have Python installed and are familiar with the language, you'll be all set to go.|The course begins with covering the fundamentals of Pandas (the library of data structures you'll be using) before delving into the most important functions you'll need for data analysis; creating and navigating data frames, indexing, visualizing, and so on. Next, you'll get into the more intricate operations run in conjunction with Pandas including data manipulation, logical categorizing, statistical functions and applications, and more. Missing data, combining data, working with databases, and advanced operations like resampling, correlation, mapping and buffering will also be covered. By the end of this course, you'll have not only have grasped the fundamental concepts of data analysis, but through using Python to analyze and manipulate your data, you'll have gained a highly specific and much in demand skill set that you can put to a variety of practical used for just about any business in the world.|The average salary for Python Developer is |$92,000| per year.|Course Objective|:|After completing this course, students will have a working understanding of:|Introduction to Pandas|IO Tools|Pandas Operations|Handling for Missing Data / Outliers|Combining Dataframes|Advanced Operations|Audience:| |This course is intended for:|Those people that need a deeper understanding of data analysis tools available today.|Prerequisites:|Students should be experienced with the basics of Python programming.|Suggested prerequisites courses:|Python for Beginners|Python Programming for Beginners|Python Object Oriented Programming Fundamentals
      $ 99.00
      One-time payment
    • Data Analysis with Python
      Self-paced with instructor - Beginner
      Data Analysis with Python from IBM. Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical ...
      Free
       
      ★★★★★ (4.6)
      (500 reviews)
    • Data Analysis: Take It to the MAX()
      Self-paced - Intermediate
      EX101x is for all of those struggling with data analysis. That crazy data collection from your boss? Megabytes of sensor data to analyze? Looking for a smart way visualize your data in order to make sense out of it? Weve got you covered! Using video lectures and hands-on exercises, we will teach you cutting-edge techniques and best practices that will boost your data analysis and visualization skills. We will take a deep dive into data analysis with spreadsheets: PivotTables, VLOOKUPS, Named ranges, what-if analyses, making great graphs - all those will be covered in the first weeks of the course. After that, we will investigate the quality of the spreadsheet model, and especially how to make sure your spreadsheet remains error-free and robust. Finally, once we have mastered spreadsheets, we will demonstrate other ways to store and analyze data. We will also look into how Python, a programming language, can help us with analyzing and manipulating data in spreadsheets. EX101x is created using Excel 2013 and Windows. Most assignments can be made using another spreadsheet program and operating system as well, but we cannot offer full support for all configurations. The goal of this course is to help you to overcome data analysis challenges in your work, research or studies. Therefore we encourage you to participate actively and to raise real data analysis problems that you face in our discussion forums. LICENSE The course materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.
      $ 99.00
      One-time payment
    • High-Dimensional Data Analysis
      Self-paced - Advanced
      If youre interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the use of the singular value decomposition (SVD) for dimension reduction and multi-dimensional scaling and its connection to principle component analysis. We will learn about the batch effect: the most challenging data analytical problem in genomics today and describe how the techniques can be used to detect and adjust for batch effects. Specifically, we will describe the principal component analysis and factor analysis and demonstrate how these concepts are applied to data visualization and data analysis of high-throughput experimental data. Finally, we give a brief introduction to machine learning and apply it to high-throughput data. We describe the general idea behind clustering analysis and descript K-means and hierarchical clustering and demonstrate how these are used in genomics and describe prediction algorithms such as k-nearest neighbors along with the concepts of training sets, test sets, error rates and cross-validation. Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts. These courses make up 2 XSeries and are self-paced: PH525.1x: Statistics and R for the Life Sciences PH525.2x: Introduction to Linear Models and Matrix Algebra PH525.3x: Statistical Inference and Modeling for High-throughput Experiments PH525.4x: High-Dimensional Data Analysis PH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays PH525.6x: High-performance computing for reproducible genomics PH525.7x: Case studies in functional genomics This class was supported in part by NIH grant R25GM114818. HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs. HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more. Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.
      $ 49.00
      One-time payment
    • Data Analysis with Pandas
      Self-paced - Beginner
      In Data Analysis with Pandas, you'll learn how to use the popular Pandas library for data analysis to explore and visualize data. In this class, we'll go throug...
      € 11.00
      Per month
    • Business and Data Analysis Skills
      Self-paced - Beginner
      In the modern workplace, it’s crucial to know how to analyze, synthesize, and tell stories with data. This self-paced career development course will help you learn how to use a spreadsheet application (like Microsoft Excel) as a powerful analytical and communication tool. You will perform real-world market and financial analyses and practice presenting your findings visually for maximum impact. By the end of the course, you will be able to make data-driven decisions that help your organization grow and prosper.This is the fourth course in Fullbridge’s four-part Career Development XSeries, designed to prepare you to succeed in the modern workplace.
      $ 60.00
      One-time payment
    • Data Analysis for Decision Making
      Virtual classroom - Advanced
      In our information age, companies have access to unprecedented amounts information on customers--their behaviors, interests, and buying habits--and the markets in which they operate. Being able to analyze that data has become a critical skill for decision makers at every level of an organization. Today’s firms use data to detect market movement before it becomes a fully-fledged trend, helping them to stay ahead of the curve, tailor products and services to specific customer segments, determine when and when to enter markets, and differentiate themselves from competitors. In this course, you will learn how to unlock the value of data to create and grow an organization. You will gain the analytical tools necessary to confidently describe the current state of areas critical to your business, predict the likelihood of an event occurring, compare two or more approaches to a business challenge, and determine if a phenomenon you are seeing is coincidence or a genuine insight. By the end of this course, you know how to make data-driven decisions to find advantages and stay competitive.
      $ 214.00
      One-time payment
    • Exploratory Data Analysis
      Self-paced with instructor - Level unspecified
      Exploratory Data Analysis from Johns Hopkins University. This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of ...
      Free
       
      ★★★★★ (4.7)
      (4,053 reviews)
    • Data Analysis Tools
      Self-paced with instructor - Level unspecified
      Data Analysis Tools from Wesleyan University. In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific ...
      Free
       
      ★★★★★ (4.5)
      (319 reviews)
    • Managing Data Analysis
      Self-paced with instructor - Level unspecified
      Managing Data Analysis from Johns Hopkins University. This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, ...
      Free
       
      ★★★★★ (4.5)
      (1,839 reviews)
    • Cluster Analysis in Data Mining
      Self-paced with instructor - Level unspecified
      Cluster Analysis in Data Mining from University of Illinois at Urbana-Champaign. Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning ...
      Free
       
      ★★★★★ (4.3)
      (145 reviews)
    • Machine Learning for Data Analysis
      Self-paced with instructor - Level unspecified
      Machine Learning for Data Analysis from Wesleyan University. Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive ...
      Free
       
      ★★★★★ (4.2)
      (204 reviews)