Data Science with Python Course in Delhi Overview IgmGuru is one of the best Data Science with Python Training Institute in Delhi which delivers a high level of quality training with the help of Industry Expert Professionals. The demand and the supply gap for a data scientist is ever increasing. In fact, in one of its surveys, IBM predicts increment in data science jobs to be 364,000 to 2720,000 in 2020 which is only going upwards in the subsequent years. Python, as a programming language, is immensely popular for building data science-based applications owing to its simplicity, and large community support and ease of deployment. IgmGuru's Data Science with Python Course in Delhi has been designed keeping in mind about learners who have zero to some level of exposure to Python. Any ideal session in this course would dedicate a good amount of time to understanding the theoretical part after which we will be moving on to the application of theoretical concepts by doing hands-on these statistical techniques. You would be provided with a lot of data set to practice things during the session and also to practice later on in the form of self-study which will help you in your journey of applied data science with python. The three main pillars of Data Science with Python Training in Delhi. 1. 2. 3. Application of mathematical and statistical concepts Expressing them using a programming language or a tool/platform Particular business domain The Data Science with Python Training in Delhi modules focuses on explaining various use cases, some of the very famous applications/services which use Python, and then we gradually move to understand data science workflow using Python theoretically. We will help you understand the basic components of any data science model, right from fetching your data from your database to building a model that is in a deployable form. What are the key deliverable's Data Science with Python Course in Delhi As you will progress in the Data Science with Python Training in Delhi, you will get to know the below things Statistics for data science Basic data cleaning techniques for model building Converting your raw data into a machine consumable format Working principle of machine learning models and their applicability Understanding the parameters required for checking model accuracy Deploying the model to make it available as a service Maintaining the model over a period of time