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Mighty Data Science Bundle

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Learn Path Description

Becoming a Data Expert is not difficult anymore! We have created this mighty bundle having 18 online courses entirely dedicated to master all the data science concepts. It is packed with courses focusing on the usage of different programming languages like Python & R, data mining, data cleaning, data analysis (especially in finance), neural networks, NLP and so much more. If these are not enough for you, then it also covers building real-world projects, TensorFlow & SAS programming. 

Skills You Will Gain

Courses In This Learning Path

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Total Duration

8.55 hours

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Level

Intermediate

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Learn Type

Certifications

Projects in R: Learn R Creating Data Science Projects

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R Programming Language is not an easy language to learn, and requires extensive practice in addition to the theory. Simply understanding in theory, how R Programming language works and everything that you can do with R is just not enough – you require a complete breakdown of how to go about doing it.This is why we have designed this comprehensive project-based course! In this course, we attempt to break down this complex programming language and environment into an easy to follow structured tutorial that will help you not only understand this statistical language, but also become more familiar with how you can go about using it.R is a programming language and environment for statistical computing and graphics. It allows developers to work with a range of statistical and graphical techniques including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, etc.Our course will help you go through a step by process of understanding how R can help you become a more efficient data miner, analyst and statistician. However, it won’t just list or show you how to do that. The instructor will lead you through real world projects that will show you exactly how you can do them, while urging you to follow all the projects along with the instructor.This project based course a great way for you to understand the fundamentals using a hands-on approach. No more confusing resources or boring theories, but rather you would actually get a hands on with the R Programming Language and environment.In this course, you would learn the fundamentals of R programming language, including the basic concepts such as lists, functions, arrays, vectors, matrices, strings, etc.There are five major aspects that you will learn in this course.1. Practical approach to the R Programming – If you already have some background in R programming, or even have the knowledge, than this will help you gain a practical approach to R programming.2. Learn Different Forms of Data Visualization – Visualizations of data has become a popular trend, as it makes the data more prominent and easier to understand. These include different types of visualizations such as bar graph, charts, heat map, etc.3. Learn efficient ways to visualize data – Data should be efficient, especially if you are working with partial data. If the data is not efficient, the analysis would not be faulty and can be misunderstood.4. Learn ways to manipulate data – Data isn’t always constant and it is often used to analyze past data and make future predictions. For this data is required to be manipulated to create predictions for multiple scenarios.5. Learn to generate reports using R – Now we come to the most important stage of data mining and analysis. Here you will learn to generate effective reports that will help you put out a clean set of data analysis for consumption.All of this and so much more in packed in this course. So, enroll now and let’s get down to programming with R!

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Total Duration

3.8 hours

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Level

Intermediate

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Learn Type

Certifications

Tensorflow for Practitioners with Python

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Computers are getting smarter, and with I pushed in to the pot, machine learning has become a prominent technological revolution that is changing how we run our devices. Devising algorithms for AIn't that easy, and require an extensive library to help them perform various tasks.TensorFlow is one such library, this open-source library is created for dataflow programming across a range of tasks. It is also a symbolic math library that is commonly used for machine learning applications such as neural networks.TensorFlow was designed by the Google team on their closed-source machine learning system known as DistBelief. This amazing system was designed to be useful in both research and commercial applications If you want to boost your career in Machine Learning and I, then this is a great system for you to learn. And because it is such a complex subject to learn, we have designed a brilliant course to help you simplify it.This course lays a solid foundation to TensorFlow, a leading machine learning library from Google I team. You'll see how TensorFlow can create a range of machine learning models, custom deep neural networks to transfer learning models built by big tech giants. You will also learn how to use and reuse tensorflow effectively and apply on industry relevant problems.Everything you learn in this course will help you get a better footing in your career, as well as help you move to much bigger and better things.What'll find in this course:Introduction to TensorFlow What is TensorFlow & why should you use it?TensorFlow as an Interface and as an environment Installing Tensorflow and becoming familiar with the interface Running your first TensorFlow program Building actual Neural Networks using TensorFlow Deepening the Networks and integrating Deep Learning Transfer Learning using Keras and TFLearn Enroll Now and start building deeper and smarter algorithms with TensorFlow.

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Total Duration

4.34 hours

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Level

Beginner

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Learn Type

Certifications

Data Science: Foundations & Regression (Python)

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  • Get your hands dirty by building machine learning models

  • Master logistic and linear regression, the workhorse of data science

  • Build your foundation for data science

  • Fast-paced course with all the basic & intermediate level concepts

  • Learn to manage data using standard tools like Pandas

This course is designed to get students on board with data science and make them ready to solve industry problems. This course is a perfect blend of foundations of data science, industry standards, broader understanding of machine learning and practical applications.Special emphasis is given to regression analysis. Linear and logistic regression is still the workhorse of data science. These two topics are the most basic machine learning techniques that everyone should understand well. Concepts of overfitting, regularization etc. are discussed in details. These fundamental understandings are crucial as these can be applied to almost every machine learning methods.This course also provide an understanding of the industry standards, best practices for formulating, applying and maintaining data driven products. It starts off with basic explanation of Machine Learning concepts and how to set up your environment. Next data wrangling and EDA with Pandas are discussed with hands on examples. Next linear and logistic regression is discussed in details and applied to solve real industry problems. Learning the industry standard best practices and evaluating the models for sustained development comes next.Final learning are around some of the core challenges and how to tackle them in an industry set up. This course supplies in-depth content that put the theory into practice.

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Total Duration

12.8 hours

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Level

Beginner

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Learn Type

Certifications

Data Science:Data Mining & Natural Language Processing in R

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MASTER DATA SCIENCE, TEXT MINING AND NATURAL LANGUAGE PROCESSING IN R:Learn to carry out pre-processing, visualization and machine learning tasks such as: clustering, classification and regression in R. You will be able to mine insights from text data and Twitter to give yourself & your company a competitive edge.   NO PRIOR R or STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement R based data science in real life. After taking this course, you will easily use packages like caret, dplyr to work with real data in R. You will also learn to use the common NLP packages to extract insights from text data.  I will even introduce you to some very important practical case studies - such as detecting loan repayment and tumor detection using machine learning. You will also extract tweets pertaining to trending topics and analyze their underlying sentiments and identify topics with Latent Dirichlet allocation. With this Powerful All-In-One R Data Science course, you will know it all: visualization, stats, machine learning, data mining, and neural networks!  HERE IS WHAT YOU WILL GET:This course will take you from a basic level to performing some of the most common advanced data science techniques using the powerful R based tools.  Equip you to use R to perform the different exploratory and visualization tasks for data modelling.  Introduce you to some of the most important machine learning concepts in a practical manner such that you can apply these concepts for practical data analysis and interpretation. You will get a strong understanding of some of the most important data mining, text mining and natural language processing techniques.  & You will be able to decide which data science techniques are best suited to answer your research questions and applicable to your data and interpret the results.After each video you will learn a new concept or technique which you may apply to your own projects.

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Total Duration

6.99 hours

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Level

Intermediate

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Learn Type

Certifications

Introduction To Data Science Using R Programming

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The power of data is undeniable, especially organized data. This is why currently data scientists rake in an average salary of over $100,000! This is also why Big Data and Data Analytics have become hot topics in today's world.All things considered we have designed this course aimed at complete beginners as well as intermediate students who want to master the art of data analytics and learn exactly how to make sense of data! The course has been designed to help breakdown everything you need to understand exactly how to get started with Data Science.While there are many other languages that can be used for data science, R has become synonymous with data analytics and has been used industry-wide in data science. R refers to the R programming language as well as R statistical computing environment that is used for statistical computing and graphics. The R language is popularly used among statisticians, data miners, data analysts, etc.In this course, we will focus on familiarizing you not only with the R programming languages basic syntax, but you also the computing environment where you will learn exactly how to import data, organize the data, create charts and graphs and also export data.The course will start by helping you learn about basic data visualizations, after which you will progress onto more advanced concepts and visualization strategies, how to generate maps, implement statistics, clean the data, how to import and export data and so much more!What you will learn in this course:Basic Data Visualization Advanced Data Visualization Generating Maps using JSON Structure Implementation of Statistics Data Munging/Wrangling Data Manipulation - Import/Export of Data into CSV or Excel Format At the end of this course, you will have mastered exactly how to clean and organize data as well as how to import and export data to R! This is the perfect course for anyone who is looking to make the jump into the world of Data Science.Not only designed for newbies, this course is also perfect for anyone who wants to brush up on their basic skills or master a new technology!So, what are you waiting for? Enroll now and learn how to harness the power of data!

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Total Duration

13.16 hours

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Level

Beginner

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Certifications

Python + Data Science: Practical Guide

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This course with a simple idea in mind:Teach you the basics of Python + Data Science in a practical way, so that you can acquire, test and master your Python skills gradually.

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Level

Beginner

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Certifications

Data Science for Beginners - Ebook

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This data science ebook helps you start with data science concepts and will provide you a complete overview of what is required to build your your skills. It covers the Data science Ecosystem and popular algorithms to help you get a complete picture of this field. Start now.

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Total Duration

5.32 hours

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Level

Beginner

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Learn Type

Certifications

Data Science for Beginners with R

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Start working on next generation Data Science projects with our latest course. Learn R programming from ground up and learn to manipulate and visualize data. This course is perfect for beginners who want to start working on Data related projects and want to build a career in data science.

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Total Duration

2.32 hours

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Level

Beginner

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Certifications

Employee Attrition Prediction in Apache Spark (ML) Project

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Spark Machine Learning Project (Employee Attrition Prediction) for beginners using Databricks Notebook (Unofficial) (Community edition Server)In this Data science Machine Learning project, we will create Employee Attrition Prediction Project using Decision Tree Classification algorithm one of the predictive models.

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Level

Beginner

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Certifications

R Programming for Beginners Ebook

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Robert Gentleman and Ross Ihaka made R a reality in August 1993. It is open-sourced and can run on any platform (Windows to Linux), and it has a vibrant community of developers and supporters. The aIR programming for beginners EUR(tm), aims to teach people the basics of the programming language. You will learn about R and Its history. Learn how to install CRAN packages. This is an important step in learning R. You will learn about the four main data types as well as the control structures. You can quickly glance at the summaries at each chapter's end, which are written in a few key points. This book is a great resource for anyone who has never used R before.

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Total Duration

4 hours

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Level

Beginner

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Certifications

Learn SAS and Become a Data Ninja

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This course is the first in my SAS training series. A Case Study at the end of the course will test your understanding!Welcome! Start this SAS tutorial online to learn SAS basics and get SAS certification. You may not understand certain aspects if you skip videos. If you only care about the import.txt lecture and not the lines of code, it may appear that some aspects are being missed. If you are studying SAS at a post-secondary institution, this course can not only help you with school projects but prepare you for a career after you complete your education.Commercially, SAS is the most used programming language. SAS is a powerful data analytic and statistical tool that can be used to help with data entry, management, and analysis. This tutorial will show you how to become a data ninja. You will learn how import different file types (.txt.csv..xlsx); how to work with data to merge two data sets, filter observations and clean and reduce your data. How to read dates and create an enumeration variables. You will also find sections on Informats/Formats, SAS Input Types, and Column Input (list input, column output, formatted input). I will be sharing some details about arrays in the arrays section. I will now show you how to use arrays to recode variables or create new ones. In the Functions section, I will cover the Rand function, length/lengthn/lengthc functions, Trim function, compress function, input/put functions, catx function and more!In the visualization section, you will learn how to make a scatter plot and bar charts. The statistical (data analysis) section will teach you how to interpret and analyze data. This section will discuss independent t-tests and chi-square analysis. It also covers linear regression and multiple regression. A few concepts from Macro programming have been added. You will also find a Case Study, which is based on a real-life application. It allows you to see how the concepts are integrated. Learning SAS programming language means that you can achieve the same goal with any software that supports SAS language. Personally, I use WPS. There are many options available to you. No risk! SAS training is risk-free! Your future looks brighter with SAS training.DISCLAIMER We are not in any way affiliated or associated with SAS Institute. We don't offer or endorse SAS University Edition downloads for learning purposes. We also do not use SAS software, SAS logos, or any other SAS software. We don't link to SAS websites, nor do they link to SAS content. Screen shots of SAS assets are not available from us. We also do not distribute them nor suggest that it is ours. WPS provides a commercial license. WPS is not associated with SAS System. The computer programming language is also referred to whenever you hear the terms "SAS", SAS Language, and "language of SAS" in my course content. My course will use phrases such as "program", SAS program, and SAS language program to refer to SAS-language programs. These programs can also be called "scripts", or "SAS scripts" (or "SAS language scripts").

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Total Duration

2.47 hours

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Level

Intermediate

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Learn Type

Certifications

SAS Predictive Modeling using Logistic Regression

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We will be using an example to show how we can predict a customer's Loan Status based on historical data (the predictors). In this course, we will work through an example where we are interested in predicting a customers Loan Status based on a bunch of historical data (the predictors).Predictive Modeling is an attractive option because it brings a ton of value to any organization. It is however more complex than other business analytics options. Predictive modeling is complex because of the many steps involved and the level of expertise required to complete some of them. These issues can be reduced or eliminated by this course.

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Total Duration

3.1 hours

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Level

Advanced

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Certifications

Advanced SAS Programming: SAS SQL, Macros, Indices

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The first section of the courses will teach you SQL in relation to SAS programming language. Also, you'll learn SAS SQL. ! SQL is used to extract/select data from databases tables and manipulate that data. This course will teach you how to improve the performance of your system by creating Indices in many different ways. You will also learn how to create macro programs that generate different reports depending on the day. Create a macro program that calculates statistics over multiple years.

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Total Duration

10.36 hours

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Level

Intermediate

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Certifications

Projects in Data Science Using R

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Data Science is a multidisciplinary field that uses scientific methods, processes, algorithms and systems for gaining insights by analyzing the structured or unstructured data. Basically, it helps in finding hidden patterns from the raw data by using technologies like R, Hadoop, Machine Learning and others.With Its use from the healthcare industry to businesses, it has one of the greatest potentials to change numerous sectors to Its entirety. Similar to the rise of data in recent years, the demands of data scientists have also exploded with average salaries being offered up to $110,000 depending upon the locality.Why you should learn Data Science?Desired in different fields like business, healthcare, finance and others In order to perform complicated data analysis To find the hidden patterns by data manipulation For making precise predictions Why you should take this course?The regular need for storing, modifying and analyzing data have made data science one of the most important field. from big to small companies, all are in a constant search for the data scientists or the individuals who understand and can work with a huge pool of data. Knowing all these facts, we have designed this comprehensive online tutorial which will help you in building different real-world projects. This tutorial with over 5 hours of videos will be sufficient enough to make you explain different aspects of data science in the most simplest, easiest and practical way.Take this course for building different real-world projects in Data Science which has great potential in the world full of data. With this course, you will learn about:Network Analysis- You will perform this concept on the pool of traffic data from a city Data Wrangling- For wrangling and visualization sports data in order to get better insights Data Manipulation- To apply all the data science concepts on historical data for having better insights on the rise and fall of empires.Forecasting- For analyzing the data to forecast commodities prices.And so much more!

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Total Duration

1.2 hour

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Level

Beginner

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Certifications

Getting Started with Data Sciences

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Do not miss out on the Data Revolution and technological advances in this age. Data Sciences is a vital skill that every businessman should have, whether they are looking to invest in new products and services or are experts in a particular field. Data Sciences are becoming more important than ever because of the abundance of data that is available on almost every device we use every day. This course will provide an overview of Data Sciences. This short course aims to cover as many Data Sciences areas as possible in a single hour. This course is for CxOs and other decision makers who are interested in investing their money in the Data Revolution. This course is for students, researchers, and anyone from any profession to help them understand the future world.

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Total Duration

1.91 hour

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Level

Beginner

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Certifications

Data Science - Python for Machine Learning

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Hands-on course using Jupyter Notebooks. All code can be found at GitHub.Students are encouraged to type the code in their own jupyter notebook as they watch the video.

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Total Duration

0.82 hour

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Level

Beginner

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Certifications

Jupyter Notebook - Big Data Visualization Tool for Data Scientist & Big data Engineers

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Jupyter Notebook: Big Data Visualization Tool for Big data Engineers and Data Scientist for an Open Source Tool (Free Source for Data Visualization)Learn the latest Big Data Technology Tool: Jupyter Notebook! And learn to use it with one of the most popular programming languages, Scala, Python, Julia, R, Ruby, and many more!One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Jupyter Notebook! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!Jupyter Notebook is an open source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.JupyterLab is a web based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible: configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular: write plugins that add new components and integrate with existing ones.Master Big Data Visualization with Jupyter Notebook.Jupyter Notebook provides a web based notebook you can use support following languages:PythonJuliaRRubyHaskellScal node.js We will Learn:Data Ingestion in Jupyter environment How to Use Jupyter to process Data in Python, Scala, Julia, R and SwiftData Discovery Data Analytics in Jupyter Data Visualization JupyterLab Jupyter Notebook How to use JupyterLab How to use Jupyter Notebook

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Total Duration

28.83 hours

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Level

Beginner

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Certifications

Learn Data Science and Machine Learning with R from A-Z

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The Learn Data Science and Machine Learning in R Course from A to Z is here! This practical course will teach you how to program in R, how to use R to analyze and visualize data, and how to make the most of it. This course will teach you how to set up and configure software for statistical programming environments. It also teaches you how to use R to perform data analysis, visualization, and code commenting. We combine theory and practical training to teach you the basics of R Programming. This course is suitable for anyone with coding experience or who wants to learn more about R programming. Adding R coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.Together we are going to give you the foundational education that you need to know not just on how to write code in R, analyze and visualize data but also how to get paid for your newly developed programming skills.The course covers 6 main areas:1: DS + ML COURSE + R INTROThis intro section gives you a full introduction to the R programming language, data science industry and marketplace, job opportunities and salaries, and the various data science job roles.Intro to Data Science + Machine Learning Data Science Industry and Marketplace Data Science Job Opportunities Introduction Getting Started with R2: DATA TYPES/STRUCTURES IN This section gives you a full introduction to the data types and structures in R with hands on step by step training.Vectors Matrices Lists Data Frames Operators Loops Functions Databases + more!3: DATA MANIPULATION IN This section gives you a full introduction to the Data Manipulation in R with hands-on step by step training.Tidy DataPipe Operator Dplyr verbs: Filter, Select, Mutate, Arrange + more!String Manipulation Web Scraping 4: DATA VISUALIZATION IN This section gives you a full introduction to the Data Visualization in R with hands on step by step training.Aesthetics Mapping Single Variable Plot Two Variable Plot Facets, Layering, and Coordinate System 5: MACHINE LEARNING This section gives you a full introduction to Machine Learning with hands on step by step training.Intro to Machine Learning Data Preprocessing Linear Regression Logistic Regression Support Vector Machines K Means Clustering Ensemble Learning Natural Language Processing Neural Nets 6: STARTING A DATA SCIENCE CAREER This section gives you a full introduction to starting a career as a Data Scientist with hands on step by step training.Creating a Resume Personal Branding Freelancing + Freelance websites Importance of Having a Website Networking By the end of the course you will be a professional Data Scientist with R and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.

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