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The 2022 Absolute Beginners Guide to Data Science

Build your mathematics and statistics foundations strongly and ensure your Data science fundamentals are in place!
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Content

Platform: Udemy
Video: 41h 38m
Language: English
Next start: On Demand

Table of contents

Description

What will I Learn and Apply post-program:
We build your foundation by going through the basics of Mathematics, Statistics and Machine Learning using our foundation training program on Data Science – DS1 Module:
In our DS1 Module You will Learn:
1)Descriptive & Inferential Statistics
2)Data Visualization
3)Python Programming
4)Data Distributions – Discrete/Continuous
5)Matrix Algebra, Coordinate geometry & Calculus
6)CRISP-DM Framework 7)Machine Learning – Part 1
8)Python Programming – Adv
9)Simple & Multiple Linear regression with case studies

A Data Scientist dons many hats in his/her workplace. Not only are Data Scientists responsible for business analytics, but they are also involved in building data products and software platforms, along with developing visualizations and machine learning algorithms
Data Analytics career prospects depend not only on how good are you with programming —equally important is the ability to influence companies to take action. As you work for an organization, you will improve your communication skills.
A Data Analyst interprets data and turns it into information that can offer ways to improve a business, thus affecting business decisions. Data Analysts gather information from various sources and interpret patterns and trends – as such a Data Analyst job description should highlight the analytical nature of the role.

Key skills for a data analyst
•A high level of mathematical ability.
•Programming languages, such as SQL, Oracle, and Python.
•The ability to analyze, model and interpret data.
•Problem-solving skills.
•A methodical and logical approach.
•The ability to plan work and meet deadlines.
•Accuracy and attention to detail.
R for Data Science:
This session is for “R for Data Science”. We will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it. In this session, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualizing and exploring data.
Why learn it?
Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines.
***What you get***

•Active Q&A support
•All the knowledge to get hired as a data scientist
•A community of data science learners
•A certificate of completion
•Access to future updates
•Solve real-life business cases that will get you the job

You will learn

✓ You will gain a firm foothold of the fundamentals of Data Science. The course provides the entire toolbox you need to become a data scientist.
✓ You will understand the mathematics and statistics behind Machine Learning
✓ You will understanding the Octagonal Technical Facets of Data Science
✓ You will start coding in Python and learn how to use it for statistical analysis
✓ You will improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation and testing
✓ You will unfold the power of deep neural networks
✓ You will carry out cluster and factor analysis
✓ You will learn how to pre-process data
✓ Impress interviewers by showing an understanding of the data science field
✓ Apply your skills to real-life business cases
✓ Learn the degrees of freedom, mathematical operations
✓ Learn the art of Data Visualization
✓ Learn Histogram, Boxplot, Scatter Plot, Co-variance and Correlation
✓ Write programs in R

Requirements

• No prior experience is required. We will start from the very basics

This course is for

• The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
• You should take this course if you want to become a Data Scientist or if you want to learn about the field
Cybersecurity, Data Science & Human Capital Practitioners!
We specialize in Cybersecurity, Data Science and Talent Management/Human capital management training. The USP of all our training’s is the hands-on that we provide, our focus is on real-life practical knowledge sharing, and not tool-based PPT slides. All our training’s are conducted by highly experienced practitioners who are dyed-in-the-wool penetration testers. The material is cutting edge and updated with even the most recent developments. We have a standard set of courses outlined in different information security domains, data analytics domains and Talent management domain. However, we also customize the training according to the clients’ requirements.
Platform: Udemy
Video: 41h 38m
Language: English
Next start: On Demand

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