Why THIS data analytics course is most preferred?

Even if you are from a non-tech background; we bet you have heard of Python, Data Analytics, Machine Learning and so on. Although these might look difficult to be cracked and hard to understand; do not let the buzzwords scare you away from choosing a field that’s trending and will be profitable in the foreseeable future.

We at Proschool want you to make a career in the most relevant field. This blog is a curation of all the basic and necessary details you will ever need to know! Don’t worry if you are a fresher; we will start by understanding what exactly these jargons mean!

What is ‘Python’?

Python is a high-level programming language that is general-purpose in nature. One of its core design philosophies is code-readability with the use of proper indentation. Proper indentation, or significant indentation, means that the indentation has a use case rather than appearing for aesthetic purposes. 

It is an interpreted language, unlike other programming languages, which are often compiled. Python has a built-in garbage collector that automatically removes unwanted objects and variables to free up memory space; this comes in handy when the code gets too long. The most commonly used variation of Python is CPython.

What is ‘Data Analytics’?

Analytics is the computational analysis of statistics and data in a systematic manner. Data Analytics can be used to discover and interpret sensible patterns in data that lead to certain results. These results can then be interpreted accordingly and used to make more effective decisions. Data Analytics is used heavily in areas with a huge amount of data, so it leads to the convergent use of statistics, data and computational power to analyze the provided data. 

Companies, corporations and organizations can benefit from using data analytics in predictive modeling and improvement of business performance. It can also be used for purposes such as marketing, management and finance, among other uses. Further ahead, we can read more about how to use the basics of Python and why Python makes sense to be used as a Data Analytics tool.

How to Use Python for Data Analytics

There are multiple ways to integrate Python into data analytics tools. One of the most common uses for Python, data analysis, comes from its ability to create and manage complex data structures – quickly, and efficiently. It offers many tools to manipulate, analyze and even represent complex data and datasets.

This representation includes datasets like time series, and even more complex structures such as merging, pivoting and slicing tables, that enable new perspectives on existing datasets. There are specific Python-based tools that provide advanced analytics combined with ML (Machine Learning).

These tools allow for the building of sophisticated models, performing more complex processing, etc. Combining this with the aforementioned extensive libraries like NumPy, you could essentially build a powerful data analytics tool from scratch. Making your own tools could require you to plug-in via an API.

Why Use Python for Data Analytics

The nature of Python is intrinsically extensible. This means that it has thousands of libraries dedicated to data analysis, including PANDAS (Python Data Analysis Library). Python libraries are mostly derived from NumPy, which includes mathematical calculations, operations and functions.

Python’s analytical tools have gained popularity due to the widespread adoption of the computing language. It is highly versatile when you need to develop multifaceted solutions. As mentioned before, Python is a truly general-purpose language. This means that you can add another layer of functionality to data analytics software, which would not be possible for other languages that have a narrower scope or lesser functionality.

Python has much better performance, and its capabilities are much higher than other popular computing languages used in data analytics. Its compatibility with other languages means that it is usually the most simple and convenient language to use. As mentioned before, Python uses relatively less memory due to its inbuilt garbage collection tool. This lightweight nature allows it to quickly outstrip other languages like MatLab or R, that while built specifically for statistical analysis, are too bulky for some use cases.

Data visualization is also a huge positive of Python, and by using multiple tools and libraries, it is possible to fully visualize the data that is being analyzed. While visualizing the data, there are two main things: 1) the objects and 2) nodes, which are the connections between the objects.

Companies Using Python Extensively

Python is used at companies like Intel, IBM, NASA, Pixar, Netflix, Facebook, JP Morgan Chase, Spotify, Dropbox and a number of other massive companies. Google uses Python as one of its four main languages, with Youtube being completely written in Python. It is also used in social media platforms utilizing algorithmic modeling, like Reddit, Pinterest, and Instagram. It was used to create the original BitTorrent client. It is heavily used in Maya, the industry standard for complex 3D Modeling.

Data Analytics: Courses, Scope, Salary and Job Demand

Some popular data analytics courses are: Data Analyst Nanodegree (Udacity), Data Analyst with R (DataCamp), Data Analytics Immersion (Thinkful), Data Science Specialization (Coursera), Business Analytics Specialization (Coursera), Excel to MySQL: Analytic Techniques for Business Specialization (Coursera), Big Data Analytics with Tableau (Pluralsight), The Data Science Course 2022: Complete Data Science Bootcamp (Udemy), Become a Data Analyst (LinkedIn Learning), Data Analytics Bootcamp (Springboard).

Business-related Data Analytics in India shows remarkable promise as an emerging field. A profession in this field offers ample scope for growth and learning. The skills required would be statistical techniques, quantitative knowledge, business acumen and learning, logical rumination, Big Data and knowledge of instruments to access the data. Asset management is also an important additional skill.

The salary for a Data Analyst in India with thorough knowledge of data analytics, ranges between ₹ 1.8 Lakhs PA to ₹ 11.5 Lakhs PA with an average annual salary of ₹ 4.3 Lakhs PA. The field is in high demand, as can be seen from the plethora of courses released by many major platforms looking to educate interested youngsters.

  • But if you are looking for a course that will train you for real world applications and help you ace that job interview; you have to check out PGCM in Data Analytics.

    This course is from one of the top rated institutes and gives a comprehensive understanding of execution. It covers the core elements of Python, Business Analytics, SQL and Machine Learning.

    If you are an aspirant, you are aware how difficult it is to get into the data driven world. You must be well prepared with the necessary tools and techniques well in advance. And there are numerous tools to learn which makes it ever more difficult to understand the learning curve.

    And so, Proschool’s PGCM is one of the most sought after data analytics courses. As it covers Python, SQL, Excel and Tableau. Another major benefit is that it provides an AICTE approved qualification which allows an exemption of a year from the MBA program.

    A very notable point here is that, unlike other certifications, it does not require the candidate to be from an engineering background or to have an in-depth understanding of tools as a prerequisite. Even if you are a complete fresher; you can still opt for this course and become a skilled professional.

    To give you a detailed insight into the same, here is the term wise syllabus that will be covered:
    Term 1:
  • Data Analysis in Excel
  • Business Statistics
  • Visualization with PowerBI
  • Introduction to IT systems
  • Business Communications
  • Marketing Management

Term 2:

  • Data handling with SQL and Python
  • Data Preprocessing and EDA
  • Intro to Machine Learning
  • Machine Learning techniques
  • Advanced Machine Learning
  • Business Simulation

On completion of the learning, two certificates are provided:
1. AICTE approved PG certificate in Management

2. NSDC certification

This course is available in both offline and online options. Now, how exactly does Proschool’s course stand apart from the others?

Here’s how:
– You earn an AICTE approved qualification which means the course material will be extremely refined
– You get a one year exception when joining an MBA course

– You will be trained by experts on even the most basic elements which will enable you to leapfrog the competition

– You will be able to understand the working and execution of Python, Data Analytics – the skills most popularly asked for by major companies today.

IMS Proschool is a good choice to pursue a Data Analytics Course because it offers:

  1. Industry relevant certifications
  2. Handpicked faculty
  3. Placement assistance
  4. Active Learning
  5. Well-Qualified Mentors
  6. Flexible Modes


All in all, there are many reasons why you should use Python for data analysis. This includes many reasons like increased flexibility, easy and gradual learning curve, open-source codebase, and well-fortified support. Python is a valuable tool for any data analyst, due to its nature for carrying out repetitive tasks, something that is seen in data analysis regularly. It handles the grunt work for the analyst while allowing them to find interesting patterns to research on. And for an ambitious aspirant PGCM in Data analytics  will prove to be the best investment of their time.