Industry-PoweredEmployability Platform

In simple form, machine learning is all about teaching the machines to learn from the data without explicitly programming. It means machines learn from data i.e. experience just the way we humans learn. Until now we thought that learning is a unique characteristic of living things. As part of machine learning you would use various algorithms and statistical models. Python programming language is widely used here. Machine learning is further classified into 3 types – Supervised, Unsupervised & Reinforcement learning. It is used in various domains such as Banking, Marketing, E-commerce, Education, Medical and so on, wherever there is data and you are interested in extracting useful insights from it for business decisions. Fraud detection, Customer churning, sales prediction, Cancel cell detection etc are a few examples of machine learning in the real life.

Data Science is a combination of Data Analytics and Machine Learning. It is all about working on the data to extract the insights from it so that the businesses could make informed decisions. Data Science course would give you the knowledge and skills required to extract the data, clean & manipulate it, use visualization techniques, develop statistical & machine learning models, etc to be the sought after professional. Imagine you are a manager at UBER. You are expected to make decisions related to the number of cars on the road, peak and non-peak pricing, predict the demand during holidays, customer churning, driver analytics and so on. It is humanly impossible to make decisions blindly without having Data Science models. This is the reason why every industry is heavily investing in data science models to be more profitable and competitive.

Data Analytics is all about extract information from the available data for decision making. It involves Statistical Analysis, Visualization, Dashboarding, Business Intelligence, etc. It mostly deals with tools such as Power BI, Advanced Excel, IBM Cognos, etc. There no or minimum programming involves. Sometimes you would find Python as part of the Data Analytics as it could be used for visualization and analysis. This field is in high demand as not every organization is interested in building whereas, everyone is interested in analysing the data for decision making. Hence, we highly recommend this course for students even those who are from non-technical field. It is good starter to enter in to the world of Data Science where you could test your skills and proceed further.

Azure/AWS DevOps is a methodology that combines software development (Dev) and IT operations (Ops). It aims to shorten the systems development life cycle and deliver high-quality software continuously. DevOps practices help organizations automate and integrate processes between development and operations teams, allowing them to build, test, and release software more efficiently and reliably. Azure DevOps is Microsoft's solution for managing the entire DevOps lifecycle, while AWS offers a set of DevOps tools to automate software delivery and infrastructure management. Both platforms provide features such as Continuous Integration (CI), Continuous Delivery (CD), automated testing, and monitoring to enhance the speed and quality of software releases.

You do not need any specific qualification to know Data Science. For that matter, it is true for any course in IT. However, you must have logical thinking, few math skills, algorithmic thinking, loads of patience and a zeal to learn. Most of these requirements could be fulfilled if you are really interested. Of course you need a good trainer or a mentor to handhold throughout your journey towards Data Science. You could start with brushing up on Statistics and learning Python. Commit to the course which is based on project-based learning as mere knowledge would not help you. Practice is the key to being good at Programming or even Data Science. That is the reasons why we give a dashboard for every learner so that they could practice their skills regularly.

Indeed it is. If you look at the amount of data we are creating on a daily basis while using social media, e-commerce, transportation, online search and even at a retail store. Organizations are interested in processing these volumes of data to get insights so that they could make business decisions such as offering personalized services to the customers or aligning their prices or launching new products or such. This is the very reason why organizations are investing heavily in Data Science models. With this, there is increasing demand for professionals with Data Analytics or Data Science certification to be part of their team and solve business problems. As per the current market trends, Data Science would create 3 times more jobs in the next decade. Hence, it is good timing to think about Data Science as a career option.

No worries. The intention is to teach Robotics and coding in a step way so that you would enjoy learning. The concepts are structured in a systematic way to facilitate learning and build confidence in your to work on the projects independently.

There are two types of courses we offer one with job readiness and the other with a job guarantee. Even though the course content, projects and approach are the same for both the programs, the only difference lies in the post completion of the course. Irrespective of what type of course you pick, with or without a job guarantee we would train you with profile building, assessments, interview skills, mock interviews and so on. We have partnership with various organizations and also our students are currently working with various reputed organizations. In the job guarantee program we would ensure and work with the learners until they are placed. You would be assigned a career coordinator who would make sure that you are placed or you would get a refund. Currently the packages for a good Data Analyst or Data Scientist could start anywhere between 5L PA to 9L PA at the entry level.