Data Analytics with Applications in Python – February 3, 4 & 11
Data analytics is increasingly becoming more important for organizations that are looking to harness their data to identify new opportunities. Understanding data helps companies make smarter business decisions, run their operations more efficiently, improve customer satisfaction and can increase their profits.
During this highly intensive program, participants will learn several data mining techniques to interpret data. Data analytics is quickly becoming an in-demand science for companies looking to become more efficient. This program is designed to solve real data science problems using Python and its library of scientific tools. In-depth knowledge of Data Mining and Machine Learning along with its corresponding coding program will equip attendees to readily apply the techniques learned in class to real work-related problems. Attendees are expected to acquire knowledge of libraries such as Pandas, NumPy and Scikit-Learn.
- Overview of Data Mining techniques
- Code along lecture on application of techniques
- Guided case study – attendees solve a case study using the methods learned in the program
Dates and Times
- February 3 from 5:30 p.m. to 8:30 p.m.
- February 4 & 11 from 9:00 a.m. to 6:00 p.m.
* Please check back soon for exact dates and times.
SF State Downtown Campus, 835 Market Street, Suite 600
Current SF State students and alumni and those who register early will receive a special discounted price of $1,095 USD.
*Program pricing and dates subject to change.
Who Should Attend
This program is designed for professionals in a variety of industry sectors who are aiming to learn Data Science and its applications in Python. Software Engineers, Tech industry individuals and managers with some basic understanding of coding will also find this program powerful and highly applicable in the real world.
- Learn some of the most famous data mining techniques
- Know how to apply the algorithms learned in the program using the most in-demand Data Science software - Python
- Be able to solve real world problems using Python
- Data cleaning and Manipulation using Python
- Data Visualization using Python
- Linear Regression Lines with Python
- Model Selection using Cross-Validation in Python
- Lasso and Ridge Regression using Python
- Logistic Regression using Python
- K-Nearest Neighbors using Python
Target Class Size
Dr. Hamed Hasheminia is an Assistant Professor and has been teaching Data Science and business analytics courses at San Francisco State University. He leads workshops with leading Data Science programs in the Bay Area. He has 3 graduate degrees (2 M.Sc. and a Ph.D.) in Industrial Engineering, Economics and Business and has experience in teaching Data Science using both R and Python. He has consulted to numerous organizations such as the largest insurance company in British Columbia, the second largest airline in Canada and to the government and the Ministry of Transportation of Canada. He is the owner of DataMiningClass.com and enjoys teaching Data Science to both Tech industry employees and university students.