The Absolute Beginners Guide to Data Science

Free Coupon Discount - The 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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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, 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 which 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 analyse, 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.

Python:

Newer data scientists gravitate toward Python because of its ease of use, which makes it accessible. So popular in fact, a staggering 48 percent of data scientists with five or fewer years experience rated Python their preferred programming language.

So, it's relatively easy to learn. However, you can see it from three different levels. Basic Python is where you get to learn syntax, keywords, if-else, loops, data types, functions, classes and exception handling, etc. An average programmer may take around 6–8 weeks to get acquainted with these basics

Python is the most common coding language we typically see required in data science roles, along with Java, Perl, or C/C++. Python is a great programming language for data scientists. ... Because of its versatility, you can use Python for almost all the steps involved in data science processes

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 become a data scientist from scratch

Why wait? Every day is a missed opportunity.

Click the “Buy Now” button and become a part of our data scientist program today.

Who this course is for:

The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills