Programming Courses

What Will I Learn?

• Use Spark for a variety of analytics and Machine Learning tasks
• Implement complex algorithms like PageRank or Music Recommendations
• Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
• Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX

Includes

• 8.5 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Requirements

• The course assumes knowledge of Python. You can write Python code directly in the PySpark shell. If you already have IPython Notebook installed, we'll show you how to configure it for Spark
• For the Java section, we assume basic knowledge of Java. An IDE which supports Maven, like IntelliJ IDEA/Eclipse would be helpful
• All examples work with or without Hadoop. If you would like to use Spark with Hadoop, you'll need to have Hadoop installed (either in pseudo-distributed or cluster mode).

Description

So, you've heard a lot about the R programming language, but you don't know how to get started?  This Udemy course is exactly what you need! This course will teach you all the fundamentals you need. Trust me, you won't need any other course to reach the intermediate/advanced level after this course.

In this course, you'll learn how do some neat programming using the popular R programming language, the most popular language of Data Science, Data Analysis, Machine Learning and so many other things..!

In this course, you can expect to become a cool R bro/sisgrammer and learn:

• The R programming environment 
• The syntax of the R programming language
• The fundamental data constructs of the R programming language
• Bar charts and scatterplots with R
• Fundamental functions with R
• Data Analysis and Data Visualization with R
• And much more...

Description

So, you've heard a lot about Tableau 10, but you don't know how to get started?  This Udemy course is exactly what you need! This course will teach you all the fundamentals you need. Trust me, you won't need any other course to reach the intermediate/advanced level after this course.

In this course, you'll learn how to make the data work for you so that you can aggregate, analyze and visualize your data. 

The course's curriculum goes as such: 

You'll get started with line and bar charts

• You'll learn to use extracts, joins and blends 
• You'll learn to advanced techniques such as Gantt charts, Treemaps, circle charts..
• You'll master row and aggregate calculations 
• You'll learn table calculations
• You'll learn to format your data for visual impact
• You'll know how to tell a story with Tableau

Requirements

• Basic programming knowledge (preferably in Python or Visual Basic)
• Prior knowledge of Maths and Statistics would be beneficial

Includes

• 4.5 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Includes

• 8.5 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Includes

• 5 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Includes

• 12.5 hours on-demand video
• 13 Articles
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Requirements

• It is recommended (though not mandated) that participants have clear understanding of high school mathematics and basic statistics

Description

Data Science - Hypothesis Testing using Minitab, R is designed to cover majority of the capabilities from Analytics & Data Science perspective, which includes the following:

• Learn how to formulate a hypothesis statements with business context
• Preform 2 sample t test for continuous output with discrete inputs in 2 categories
• Using ANOVA for continuous outputs with more than 2 discrete categories of inputs
• Performing 2 – proportion test for discrete output and discrete inputs in 2 categories
• The Chi – Square test for discrete outputs with multiple discrete inputs 
• Introduction to Non Parametric tests like: Mann Whitney test, Paired T test, Moods median Test and Tukey pairwise comparisons  
• Learn about Hypothesis testing techniques & how to accomplish the same using R and Minitab

What Will I Learn?

• Build machine learning model, including training, exporting, and app development.
• Build and run Python projects.
• Build complete computational models.
• Use different machine learning mechanisms and commonly used algorithms.
• Train and test models to use for future predictions.
• Build your first Android Studio and Mac apps today.
• And more!

Includes

• 23 hours on-demand video
• 21 Articles
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Includes

• 4.5 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

What Will I Learn?

• Use Python for Data Science and Machine Learning
• Use Spark for Big Data Analysis
• Implement Machine Learning Algorithms

Includes

• 22 hours on-demand video
• 9 Articles
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

What Will I Learn?

• Code in the Python 3.5 programming language.
• Make games with Python.
• Create basic line and scatter plots with Matplotlib 1.5.
• Read finance data directly from Yahoo.
• Customise our graphs with visuals, a title, labels, text and a legend.
• Recognize types of visualization: histograms, pie charts, and box and whisker plots.
• Make candlestick plots.
• Understand figures and subplots.
• Perform in-depth customization of plot structure
• Understand basic 3D plotting.

Includes

• 27 hours on-demand video
• 3 Articles
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Requirements

• Download Anaconda 4.2.0, the free data science platform by Continuum, which contains Python 3.5.2 and Matplotlib.
• Otherwise, you can download and install Python 3.5.2 and Matplotlib for free online.
• Topics involve intermediate math, so familiarity with university-level math is helpful.

Requirements

• Some basic knowledge of R is expected. However this course does include a quick overview of R knowledge required for this course.

Requirements

• Python Programming Skills
• A computer with decent memory & internet connection
• Either Ubuntu, Mac OS, or Windows as an operating system

What Will I Learn?

• Connect Twitter and R to harvest Tweets for certain keywords
• Perform sentiment analysis based on a simple lexicon approach
• Clean and process Tweets for further analysis
• Export text based data and sentiment scores from R
• Use Tableau to visualize sentiment analysis data
• Identify situations where sentiment analysis can be applied in a company

What Will I Learn?

• Know how to answer all of their marketing-related questions using a SQL query
• Understand what a relational database is
• How to install SQL on Mac, Linux, or Windows
• How to create a table
• How to import data into a table
• How to query a table
• How to insert into, update, and delete from a table
• Speed things up using indexes
• Join tables together to merge data
• Aggregate data using count, sum, and average
• Determine where in the sales funnel customers are being lost
• Chart your year over year revenue
• Group and sort sales by location
• Use SQL on Spark
• Install Spark
• Create a Spark cluster on AWS EC2

Includes

• 7 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Includes

• 5.5 hours on-demand video
• 2 Articles
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

Requirements

• Experience in using a Computer - Windows/Linux/Mac
• Basic Mathematical Knowledge

Includes

• 8.5 hours on-demand video
• Full lifetime access
• Access on mobile and TV
• Certificate of Completion

What Will I Learn?

• Understand the Basics of Data Science.
• Learn how to debug and fix machine learning models.
• Know and understand how to use popular data science tools.

Requirements

• Know how to use a computer (MAC or Windows).
• Exposed to Computer Programming (in any language) preferably Python.
• Know Basic Statistics (mean, std, median, etc.)

What Will I Learn?

• What is Effective Data Science?
• How to assess your current skills in Data Science?
• How to identify the right skills to focus on?
• What are the skills required for Effective Data Science?
• How to communicate so your data products are used?
• How to find and define Data Science use cases properly?
• How to manage a Data Science project effectively and efficiently?
• How to design good Data Science products with Quality code?
• How to continuously learn and practice in the field of data science?
• How to learn from Data Science Experts?
• How to find and do good Data Science projects?

What Will I Learn?

• Experienced with N-dimensional array, Series, and DataFrame
• Perform data analysis with python 3
• Be very confident when using Pandas and Numpy
• Gain extensive knowledge of how pandas works