The Data Mining, Analysis, and Statistics Masterclass

Course details

Do you want to build data science projects? This course is for you!

Data is the future. Everyone should know how to understand, handle, and express data. Enroll in this ultimate guide and get the competitive edge in any field.

Funded by a #1 Kickstarter Project by Mammoth Interactive

Part 1: Python Programming Fundamentals

• Code in Python, a general purpose coding language used for everything like YouTube to data science.

• Make games with Python.

• Learn to visualize data directly in code

• And more!

You willlearn the basics of programming, including topics like variables, functions, and if statements. You'll learn about data structures such as lists, dictionaries, and sets. You will be able touse 'for' and 'while' loops, how to handle user input and output, file input and output.

With Mammoth Interactive you willapply your knowledge to build a fully functional tic-tac-toe game and Blackjack game.You'lllearn to useclasses, methods, attributes, instancing, and class inheritance. You will be ableto solve errors that can occur when you work as a programmer.

Part 2:Data Visualization Projects

• Learn to use the Python 2D and 3Dplotting library Matplotlib

• Apply your newPython knowledge to Matplotlib.

• Learn tomake line plots, scatter plots, candlestick plots.

• Read finance data directly from Yahoo.

• Customize visuals on agraph

• Add text and annotate graphs.

Part 3: Data Analysis Tools with pandas

You will learn how to usepandas, anopen source library with high-performance and easy-to-use data structures and data analysis tools written for Python.

• Create and manipulate dataframes with pandas.

• Apply Python to thepandas framework.

• Create and expand dataframes.

You'll learn how to get values from data and how to handle NaN values. You'lllearn how to read and write data from and to the comma-separated values (CSV) file format.

Then we will take different approaches to analyzing data. And much more in this huge Mammoth Interactive course.

Included in this course is material for beginners to get comfortable with the interfaces. Please note that we reuse this content in similar courses because it is introductory material. You can find some material in this course in the following related courses:

• Data Mining with Python! Real-Life Data Science Exercises

• Crack Pandas and NumPy: Python Data Science Made Easy

• Data Science & Analysis: Make DataFrames in Pandas & Python

• Learn Python Data Analysis with Pandas and Make a Unity Game

• Make 2D & 3D Graphs in Python with Matplotlib for Beginners

• Python Data Science and Machine Learning Bootcamp with Keras

• Making Games in Unity and Graphs in Python using Matplotlib

Part 4: Data Mining withClassifying,Plottingand Analyzing Statistics

You will learn to create, evaluate and use data models to make predictions. Enroll now to learn data classification, visualization, plotting and statistical analysis.

Learn To Build Predictive Models

Practice for real world projects such as: learn how to find data on a house when looking to become a homeowner. You will be able to look through house data to find useful information from a text dataset.

• Detect outliers in univariate, multivariate and high dimensional spaces

• Learn how to use Apache Spark, the number one framework used for distributed processing.

• And many more topics explained with concrete examples.

• Use a practical dataset to learn data wrangling.

• Clean data, filter noise, andmake data available for analysis.

• Perform simple statistics with a range of examples.

• Use the K-NN classifier and SVM.

You will learn association, correlation, and detecting outliers in univariate, multivariate and high dimensional spaces. You will also learn dimensionality reduction.

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