Learn Data science & Business Analytics-Real life case study

About this course

Let me tell you the foundation of Data Science. Its Statistics.If Data is the new oil of the 21st century, then Statistics is the engine which drives the Vehicle of Data Science. And guess who is the driver, well it's the person who knows statistical concepts and one who can apply these concepts in solving real life problems. Well that is what the future of Data science is going to be.I regularly guide my students to pursue industry relevant skills in data science. And the core skill which is in demand across every profession be it Business, Finance, Engineering, Social Science, Psychology : Statistics.Now knowing only the concepts of statistics would not serve much in the highly competitive industry. Thus I have designed this course integrating Theory with practical real life examples.We are going to solve the real life problems through Microsoft Excel, Validate the results through Excel, Draw the charts & graphs beside the core analytics component of the course.And for the surprise you will get some glimpses of R programming in one of the lectures ( just to let you know that its not something to be feared )The course curriculum includes:Probability Distributions (Discrete & Continuous)Sampling Theorem ( Sampling Distribution of sample Mean,Central Limit Theorem Sampling distribution of sample proportion)Confidence IntervalHypothesis TestingRegression Analysis (Simple & Multiple Regressions)During the course we will be engaging in interactive discussions while understanding tough but important concepts of statistics.We will solve some real life examples in the process. And we will also be providing you with the lecture notes, Excel files  for easy revision . To get the overview of my teaching methodology I recommend you to click on preview lecture and decide for yourself whether its worthwhile to do this

Course objectives

• Integrate theory with practical application in data science
• Enhance industry-relevant skills in statistics and data analysis
• Encourage interactive discussions to clarify complex concepts