Instructor-led interactive sessions
Well-equipped training platform
Certified Data Science Practitioner Course Learnings
In this course, you will implement data science techniques in order to address business issues. You will:
• Use data science principles to address business issues.
• Apply the extract, transform, and load (ETL) process to prepare datasets.
• Use multiple techniques to analyze data and extract valuable insights.
• Design a machine learning approach to address business issues.
• Train, tune, and evaluate classification, clustering, regression, and forecasting models.
• Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.
Data Science Practitioner Audience
This course is designed for business professionals who wish to leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations.
Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business.
Eligibility Criteria for Data Science Practitioner Training
• A high-level understanding of fundamental data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science
• Experience with high-level programming languages like Python. Being comfortable using fundamental Python data science libraries like NumPy and Pandas is highly recommended.
• Experience working with databases, including querying languages like SQL.
Data Science Online Training
Virtual Instructor-Led Training
- 4 days Instructor-led Online Training
- Experienced Subject Matter Experts
- Approved and Quality Ensured training Material
- 24*7 leaner assistance and support
Customized to your team's need
- Blended Learning Delivery Model (Self-Paced E-Learning And/Or Instructor-Led Options)
- Course, Category, And All-Access Pricing
- Enterprise-Class Learning Management System (LMS)
- Enhanced Reporting For Individuals And Teams
- 24x7 Teaching Assistance And Support
a) Initiate a Data Science Project
b) Formulate a Data Science Problem
a) Extract Data
b) Transform Data
c) Load Data
a) Examine Data
b) Explore the Underlying Distribution of Data
c) Use Visualizations to Analyze Data
d) Preprocess Data
a) Identify Machine Learning Concepts
b) Test a Hypothesis
a) Train and Tune Classification Models
b) Evaluate Classification Models
a) Train and Tune Regression Models
b) Evaluate Regression Models
a) Train and Tune Clustering Models
b) Evaluate Clustering Models
a) Communicate Results to Stakeholders
b) Demonstrate Models in a Web App
c) Implement and Test Production Pipelines
Data Scientist Aspirant
Anup Kumar Mishra
This Data Science course is of 4 days duration.
No, there are some prerequisites you need to fulfill. Please check the eligibility criteria.
Vinsys provides regular tests, mock practice sessions, and instructor-led training and provides extensive support while learning.
This course is also designed to assist students in preparing for the Certified Data Science Practitioner certification.
No, it is an instructor-led online course.