Customer Analytics in Python 2020 is a comprehensive customer analysis training course in Python using PCA methods, K-mean clustering, reactionary modeling and deep neural networks . In the economy, the High present-day science, data and marketing, the key for companies that want to position themselves in the tops, retain, and analysis of the client is exactly where these two forces together are . This course is accompanied by extensive knowledge of data science and exciting methods that companies use and implements all of them in Python training . Mastery of these knowledge and skills, with regard to job opportunities income high that in the field of science data, there is also change and transformation, the Marketing Department of many companies in order to use this knowledge can be very advantageous to be.
According to the extent of the content in this period, its topics are divided into five sections . The first part of the … familiar with the concepts and theories related to IS and then in the second part, the analysis of clustering and reduce the dimension in the direction of the segmentation of customers to help algorithm the K-means algorithm and analysis of principal component ( PCA ) training and package popular, such as NumPy and scikit-learn is used . The third section also focuses on applying descriptive statistics as an exploratory part of the analysis, which is very effective in interpreting customer behavior . In the fourth section, rebound modeling is implemented for the possibility of purchase, purchase quantity and brand selection . In this section, linear and logical regression is also used using the sklearn library . Finally, in the fifth section, deep learning power is used to predict future behavior using artificial neural network and TensorFlow 2.0 framework .
What things to learn
Professional mastery of customer analysis – Preliminary to advanced
Familiarity with the most important analysis used in medium and large companies
Understanding the basics of marketing modeling theory: segmentation, targeting and …
Perform K-mean clustering, PCA and their composition
Modeling the probability of purchase, number of purchases and brand selection by customers
Optimize the results of neural networks
This training suits people who
People seeking employment in the field of data science or business intelligence
People who are interested in numbers and quantitative analysis
People who are engaged in data science and want to expand their skills
People who are engaged in marketing and want to strengthen their career by mastering data science
Profile Customer Analytics in Python 2020
Lecturer: 365 Careers , 365 Team Careers
Training level: intermediate
Number of lessons: 77 lessons in 13 sections
Duration: 5h 10m
- You’ll need to install Anaconda. We will show you how to do it in one of the first lectures of the course
- Basic Python programming
- A willingness and enthusiasm to learn and practice
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