(NP2001S1): Introduction to PYTHON & Data Analysis
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The Global Data Analytics Market has witnessed strong, continuous growth in the past few years and is projected to continue this same path. With the help of data analytics, organizations can now leverage data to extract valuable insights, which are used to create actionable decisions. In the past few years, data analytics has been broadly used to empower organizations to make the most profitable business choices. A recent market study shows that the Data Analytics Market is expected to grow at a CAGR of 30.08% from 2020 to 2023, which would equate to $77.6 billion. In 2019, the global analytics market was $49 billion worldwide, which is more than double the value four years ago.
Welcome to the first step of the “Specialization in data analytics with PYTHON”. In this course, students will be introduced to the PYTHON programming language and the concept of data analysis. How data analysis has become one of the most important skills for students in different areas. How data analysis and PYTHON, is useful in every domain, ranging from mathematics to physics, from computer science to electrical engineers. Every second company works with data, and so, requires, professionals, who can understand their data and can play with them! This course will bring out the understanding and motivation to start a career in data analysis using PYTHON.
What are the learning outcomes?
By the end of the course, students will be able to understand the following:
Get to know the PYTHON programming language.
Understand how PYTHON is famous among the existing programming language solutions
Deep understanding of the concept of data analysis
Go through the main steps of data analysis and their types.
Understand why PYTHON is considered as one of the best solutions for data analytics
Observe the current job markets in the area of PYTHON and analytics and how this market trend will increase, with an increase in requirement for data analysts.
Guided through the installation process of the most essential software tools.
Finally, prepare yourself for the beginning of practical PYTHON and data analysis.
What will you learn?
Module 1: What is PYTHON and why it is so famous?
In this module, students will come to know about PYTHON, as a programming language, and how, it turned out to be one of the most important languages in the world. This module will help students to understand the language from scratch, irrespective of their past professional experience.
Students will be given the task of sharing their possible applications of data analytics and PYTHON programming language. Such a task will help students to widen their imagination and applicability of data analytics in their respective fields.
Specific topics to be covered:
Some history of PYTHON
How PYTHON is so famous?
PYTHON is slow! Yet faster!
Why so famous?
Module 2: What is data analysis?
In this module, students will see what exactly a data is, for an engineer. And what kind of data suits your needs. How to get the understanding, in order to get the required hidden information from any level of datasets. This module will also discuss the skills required for anyone interested in pursuing a career in this field.
Specific topics to be covered:
Introduction to data analysis and definitions
Types of data analysis
Steps for data analysis
Module 3: Why PYTHON for data analysis
In this module, how a programming language enables us to understand the data and retrieve the information we want. Students will understand why PYTHON is the most used language and how PYTHON is one of the best available languages for implementing data analytics.
Specific topics which will be covered in these modules are as follows:
Why PYTHON for data analysis?
More details to convince you!
PYTHON vs R
Process of data analysis
Module 4: What data analysts do?
In this module, students will understand the average profile of a data analyst. Students will be shown how the implementation of data analysis changes with the different field, a student is working on. This virtual tour will help students to correlate themselves with different domains of work areas.
Main areas to be focussed in this module are:
Types of data analysis
Skills and purpose
Module 5: Application areas
In this module, we will discuss the numerous ways, a student could play with data. We will discuss different job domains and their growing needs for data analysts.
Students will be following the following sections:
The Indian job market for data analytics
Job growth and predictions!
Areas you can work
There is scope for everything and everyone!
Existing application areas
Module 6: Necessary pre-requisites and software requirements
In this module, we will discuss, the basic mathematical understanding, the student should have, before beginning with data analysis. However, his course, consider assumes that student has nearly zero knowledge of PYTHON language. We will discuss the necessary tools and software as well.
The main covered areas will be:
Basic software tools
Optional future tools
Guide to install software
All ready to begin the practical work!
What are the main highlights of the program?
Learn without a career break with online classes available 24*7.
One can access the course at their own pace, but with the investment of 3-5 hours/week, it can be finished within a month.
The program uses a Continuous Evaluation System that assesses the learners over convenient and regular intervals. Such a system provides timely and frequent feedback and helps busy working professionals stay on course with the program.
The education delivery method is a blend of classroom and experiential learning.
How to enrol?
Signup with your operational e-mail ID.
Select “(NP2001S1): Introduction to PYTHON & Data Analysis“.
Select “Take the Course“.
Apply coupon code if applicable.
Fill the required fields on the form.
Select your preferred payment gateway.
Pay the total amount.
Select “Start Course” and gear up on skilling mode.
Who should apply?
The program is designed for students or professionals who are:
Having a Diploma, BE / B.Tech or equivalent in domains such as Automotive, Mechanical, EEE, ECE, Instrumentation, Mechatronics.
Designing enthusiasts (No academic qualification mandatory)
Working in industries such as Automotive, Auto component, Design, Manufacturing, etc.
Working in Functional areas such as R&D, Analysis, Maintenance, Projects, component design, etc.
Interested in pursuing further studies on the part-time or full-time basis in Design and Engineering Sector.
What are the technical requirements?
The program to give its best will need the following requirements:
Computer/ Laptop will provide you with the best experience, but this program is quite compatible with smartphones to make it feasible for students worldwide.
High-speed internet for crystal clear experience, but this program can also run without buffering with below-average connectivity for reaching out to students from suburban and rural areas.
A student should make their notes for future reference.
Applicant should have basic knowledge about high-school physics, maths, and chemistry, even though the pre-requisite of this program will brush up one’s basic concepts.
A student should have a compatible computer for PYTHON software so that they can practice with the progress of the course.
DIYguru will feel proud to awards the certificate of competency in ‘Introduction to PYTHON & Data Analysis’ to only those aspirants who have 100% completed their online module.
DIYguru proficiency Certificate is highly valuable by industry giants namely Robert Bosch; Maruti Suzuki; Hyundai Motors, are the name of few, which is why DIYguru earned certificates are secured with a unique certificate ID. To check the validation of the certificate, check out the footer section of the home page.
Certificate provided to you is an online certificate, which means there is no need to download, after completion of the course, aspirants are requested to check their profile to view their earned certificate. In case the certificate is not issued feel free to write us a email@example.com, our team will help you out.
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