Udemy - House Price Prediction using Linear Regression and Python

Our course ensures that you will be able to think with a predictive mindset and understand well the basics of the techniques used in prediction.
Critical thinking is very important to validate models and interpret the results. Hence, our course material emphasizes on hardwiring this
Requirements
To get started with Predictive Modelling with Python a solid foundation in statistics is much appreciated. It takes a good amount of understanding to interpret those numbers to understand whether the numbers are adding up or not.
Along with the above-mentioned knowledge, one must know to code in Python.
Knowing SQL also acts as a complementary skillset.
Even if someone is not well equipped with the above-mentioned skill, it should not act as a hindrance as everything is possible with an honest effort and strong will.
Description
Predictive modeling is a field which has immense growth in line in due years to come due to the definite explosion of data that we are noticing. In the year 2017, it was forecasted by IBM that the demand for data scientists and analytical professionals will grow by 15% in the year 2020. Many companies have realized the importance of using predictive modeling for their business but currently, there is a shortage of skilled professionals. A substantial amount of salaries is offered to people with this skillset because of the nature of the job. The demand for qualified candidates is increasing at a significant rate. It is the right time to invest in learning for such a niche skill as the market for predictive analytics is not coming down any sooner.
It is the use of data and statistics to predict the outcome of the data models. This prediction finds its utility in almost all areas from sports, to TV ratings, corporate earnings, and technological advances. Predictive modeling is also called predictive analytics. With the help of predictive analytics, we can connect data to effective action about the current conditions and future events. Also, we can enable the business to exploit patterns and which are found in historical data to identify potential risks and opportunities before they occur. Python is used for predictive modeling because Python-based frameworks give us results faster and also help in the planning of the next steps based on the results.
Our course ensures that you will be able to think with a predictive mindset and understand well the basics of the techniques used in prediction. Critical thinking is very important to validate models and interpret the results. Hence, our course material emphasizes on hardwiring this similar kind of thinking ability. You will have good knowledge about the predictive modeling in python, linear regression, logistic regression.
Who this course is for:
This Predictive Modeling with Python Course can be taken up by anyone who shares a decent amount of interest in this field. The earlier someone starts the further they can reach. In the case of students who are pursuing a course in statistics, or computer science graduates it is a very good opportunity to direct your career in that direction. As this is a much demand skill every IT professional is looking for a good switch and entering the domain of predictive analysis.
After successfully having hands-on with Predictive Analysis you get open up career opportunities within job roles like that of a Data Analyst, Data Scientist, Business Analyst, Market Research Analyst, Quality Engineer, Solution Architect, Programmer Analyst, Statistical Analyst, Statistician, etc.

Homepage

https://www.udemy.com/course/house-price-prediction-using-linear-regression-and-python-examturf/