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Certified Data Science Practitioner Certification Training
Certified Data Science Practitioner Certification Training
Become a Certified Data Science Practitioner and Embark on a Path to Success!
Data handling skills lay the foundation for a successful business because data is crucial to understand previous trends and future scope. Precisely, data is essential to understanding where the business is hea
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Certified Data Science Practitioner Course Overview
Certified Data Science Practitioner is a 5-days course that explains you the important concepts of data science via 8 short modules. You will learn to address business issues using data; you will explore data distribution and analyze data; you will design a machine learning approach, and lot more. The best aspect is that this course includes hands-on activities to help you understand the application of data science in dynamic business contours. You will develop regression and clustering models, and finally undertake a data science project to learn all intricacies minutely.
This course is also designed to assist students in preparing for the Certified Data Science Practitioner certification.
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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.
Course Outline
Module 1: Addressing Business Issues with Data Science
a) Initiate a Data Science Project
b) Formulate a Data Science Problem
Module 2: Extracting, Transforming, and Loading Data
a) Extract Data
b) Transform Data
c) Load Data
Module 3: Analyzing Data
a) Examine Data
b) Explore the Underlying Distribution of Data
c) Use Visualizations to Analyze Data
d) Preprocess Data
Module 4: Designing a Machine Learning Approach
a) Identify Machine Learning Concepts
b) Test a Hypothesis
Module 5: Developing Classification Models
a) Train and Tune Classification Models
b) Evaluate Classification Models
Module 6: Developing Regression Models
a) Train and Tune Regression Models
b) Evaluate Regression Models
Module 7: Developing Clustering Models
a) Train and Tune Clustering Models
b) Evaluate Clustering Models
Module 8: Finalizing a Data Science Project
a) Communicate Results to Stakeholders
b) Demonstrate Models in a Web App
c) Implement and Test Production Pipelines
Choose Your Preferred Mode
Data Science Online Training
- 4 days Instructor-led Online Training
- Experienced Subject Matter Experts
- Approved and Quality Ensured training Material
- 24*7 leaner assistance and support
Corporate Training
- 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
FAQ’s
What is the Data Science Practitioner course duration?
This Data Science course is of 4 days duration.
Is this Data Science Practitioner course suitable for beginners?
No, there are some prerequisites you need to fulfill. Please check the eligibility criteria.
Why choose Vinsys for this course?
Vinsys provides regular tests, mock practice sessions, and instructor-led training and provides extensive support while learning.
Will I get any exam assistance for Data Science Course?
This course is also designed to assist students in preparing for the Certified Data Science Practitioner certification.
Is the Data Science Practitioner course offline?
No, it is an instructor-led online course.
Why Vinsys
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3,000+ Courses & 2,000+ Modules
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Reviews
Learning data science concepts was like a dream come true, and my 5-day journey became more fruitful with exceptional support from the Vinsys trainer. The faculty was friendly and encouraged inquiry during the sessions that helped me fetch the most out of this course. Thanks, Vinsys.
Rachana VasisthData Scientist Aspirant
I could see the difference when one of my team members finished this course. His concepts were clearer, and so was his motivation to implement data science for the betterment of organizational procedures.
Anup Kumar MishraData Scientist
