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What is Flexi Pass?
Python is a multi-paradigm or versatile programming language that can be considered as a sort of swiss knife for the coding world. This is because it supports structured programming, Object Oriented Programming, and even functional programming patterns. The versatility of Python undoubtedly makes it the best-suited programming language for the data scientists. Here are some of the other advantages of python for data science, which will help you understand why you should learn data science with Python:
All the above mentioned advantages of Python programming language make it ideal to be used for data science by the data scientists. Owing to the extensibility and general purpose nature, it is recommended that you learn data science with Python.
The course includes four real-world, industry-based projects. Successful evaluation of one of the following projects is a part of the certification eligibility criteria:
Project 1: Products rating prediction for Amazon
Amazon, one of the leading US-based e-commerce companies, recommends products within the same category to customers based on their activity and reviews on other similar products. Amazon would like to improve this recommendation engine by predicting ratings for the non-rated products and add them to recommendations accordingly.
Domain: E-commerce
Project 2: Demand Forecasting for Walmart
Predict accurate sales for 45 stores of Walmart, one of the US-based leading retail stores, considering the impact of promotional markdown events. Check if macroeconomic factors like CPI, unemployment rate, etc. have an impact on sales.
Domain: Retail
Project 3: Improving customer experience for Comcast
Comcast, one of the US-based global telecommunication companies wants to improve customer experience by identifying and acting on problem areas that lower customer satisfaction if any. The company is also looking for key recommendations that can be implemented to deliver the best customer experience.
Domain: Telecom
Project 4: Attrition Analysis for IBM
IBM, one of the leading US-based IT companies, would like to identify the factors that influence attrition of employees. Based on the parameters identified, the company would also like to build a logistics regression model that can help predict if an employee will churn or not.
Domain: Workforce Analytics
Project 5: NYC 311 Service Request Analysis
Perform a service request data analysis of New York City 311 calls. You will focus on data wrangling techniques to understand patterns in the data and visualize the major complaint types.
Domain: Telecommunication
Project 6: MovieLens Dataset Analysis
The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The researchers of this group are involved in several research projects in the fields of information filtering, collaborative filtering and recommender systems. Here, we ask you to perform an analysis using the Exploratory Data Analysis technique for user datasets.
Domain: Engineering
Project 7: Stock Market Data Analysis
As a part of this project, you will import data using Yahoo data reader from the following companies: Yahoo, Apple, Amazon, Microsoft and Google. You will perform fundamental analytics, including plotting, closing price, plotting stock trade by volume, performing daily return analysis, and using pair plot to show the correlation between all of the stocks.
Domain: Stock Market
Project 8: Titanic Dataset Analysis
On April 15, 1912, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This tragedy shocked the world and led to better safety regulations for ships. Here, we ask you to perform an analysis using the exploratory data analysis technique, in particular applying machine learning tools to predict which passengers survived the tragedy.
Domain: Hazard
Alvaro is a Data Scientist who founded Quant Company and has also worked as a lead Economic analyst in the Central Bank of Guatemala. He is a M.S. in Quantitative Economics and Applied Mathematics and is actively involved in consulting and training in the data science space.
Simplilearn's Data Science with Python training was a great experience. Their trainers are the best that I have come across since I started learning with Silplilearn. He is always prepared for class with a well-documented note session which is also useful for hands-on learning after class to enhance the learning experience. Thanks Simplilearn. This is the best platform that I have come across.
Read more Read lessI just completed 3 classes under this program - Data Science Using SAS, R and Big Data Hadoop and Spark Developer. I am currently enrolled in Python training. What I like the most is that the live recordings from each class are lifetime references for us to review in the future. The self-running videos in each topic were also very useful as they cover theory which might not have been covered during the live classes. I have made significant gains so far in my knowledge of key technologies and tools in Data Science. Together with electives offered under this program, I will eventually be getting a comprehensive foundation training in Data Science.
Read more Read lessPrior to joining Data Science course with Simplilearn, I had little knowledge about it. The certification helped me to understand the Machine Learning, Web Scraping, Natural Language Processing in detail. The trainer was very helpful and was always there to guide me in every step. The certification helped me to enhance my career from Software Engineer to Associate Consultant with a salary hike. I am planning to take a few more course from Simplilearn in future.
Read more Read lessI have enrolled for Data Science certification from Simplilearn. The course materials are great and the trainers are also very helpful. The industry-based project is the best part of the course. Simplilearn is better than any others in the market.
Read more Read lessI had joined the Data Science certification from Simplilearn. The course content was really good. The trainer puts a lot of efforts into explaining every detail which made the learning very absorbing. The customer support is always available whenever you need help. I actually feel one step forward towards my goal. Thank you.
Read more Read less* The projects have been built leveraging real publicly available data-sets of the mentioned organizations.
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