Business Analytics using Python is a five-day instructor-led classroom course. The course graduates from basic level to advanced topics carefully designed to make it ideal for candidates with or without prior experience in Python programming and data analytics. Topics covered include the basics of Python programming, supervised learning methods which will cover linear and nonlinear techniques, decision tree, k nearest neighbour, support vector machine and clustering.
- An interest in and flair for numbers
- Willingness to learn statistics
- Awareness on the basics of any programming language
Who Should Attend?
- Working professionals who are interested in upskilling or reskilling in the area of machine learning
- Aspirants from Science, management, engineering, economics or commerce background who wish to pursue a career in machine learning
- Professionals in finance, marketing, sales, HR, production, quality and operations who wish to apply data analytics skills in their current jobs to derive quantitative insights
You do not need any prior experience in data analysis to attend this course. Awareness of programming is required to participate in this course, which will make the learning process faster. The instructors hand hold participants through the fundamentals of Python scripting and introduce them to the world of analytics. The aim of the course is for participants to have a thorough grasp of advanced machine learning concepts.
- Working knowledge in machine learning with hands-on Python experience
- Skills to build machine learning models in data analytics
- Skills required to build data models using supervised and unsupervised methods
- Insights on deriving hidden information from voluminous and complex data
- Certification of completion on successfully completing the course requirements
Understanding Data Analytics
Importance of data in business
Data analytics ecosystem
Basis of Python programming
Basics of Python
Variables and Operators
Lists, Dictionary and Functions
Programming in Python
Introduction to Machine learning
K Nearest Neighbor
Gradient Boosting algorithms
Support Vector Machine
Clustering techniques – K means clustering
Duration: Five days
Training locations: Bengaluru, Delhi, Mumbai, Pune, Hyderabad, Kolkata, Chennai
Call us : +91 9061 342 432 (Raynette Furtado)
Mail us : firstname.lastname@example.org
|August 2018||20 - 23||Bengaluru|
KPMG in India reserves the right to restrict the number of participants per batch and cancel or postpone any batch.