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Certified Data Science Practitioner Certification Training

Join us on this journey to become a certified Data Science Practitioner, which validates your skills in analyzing vast datasets, extracting insights, and leveraging them to fuel organizational advancement. The learners can examine data and identify appropriate methods for visualization while also

Duration Duration : 5 Days
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Certified Data Science Practitioner Certification Training
  • training
  • ae
  • Domain / Vendor
  • certified data science practitioner certification
E-learning structured around practical workshops with real-world scenarios.
Practical insights into data management and interpretation
Access comprehensive course structure with self-paced learning options.
Master course concepts through case studies and interactive activities
OverviewLearning ObjectivesWho Should AttendPrerequisiteOutlineCertification

Course Overview

The Instructor-led, intermediate-level course on Certified Data Science Practitioner (CDSP) spans five days and covers eight units. In our data-centric era, a thriving business must recognize data as a vital asset for navigating its current state and future trajectory. Data not only unveils insights but also serves as a compass, shaping decisions and operational strategies on a daily basis.

An individual who is a certified Data Science Practitioner can use the information from the data and apply it to improve an organizations efficiency using artificial intelligence and different statistical models. This course ensures you can analyze, comprehend, manipulate, and present data within a structured and consistent framework.

This certification will confirm that the candidate has the requisite knowledge, abilities, and proficiencies to address queries by collecting, manipulating, and analyzing data sets. It involves leveraging statistical models and artificial intelligence algorithms to effectively extract and articulate knowledge and insights. This course equips you to contribute tangible value to your organization by translating data science principles into actionable strategies.

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Course Objectives

This course facilitates learners in attaining comprehension of the following objectives:

  • Apply fundamental concepts of data science 
  • Use data visualization techniques to extract information
  • Analyze and transform the data from various sources
  • Apply statistical methods and machine learning algorithms to analyze data sets
  • Develop problem-solving skills by applying data science techniques
  • Identify and integrate classification models
  • Evaluate different models of regressions, forecasting, and clustering
  • Implement the ETL (Extract, transform and load) process to preprocess and cleanse datasets

Audience

This course will be beneficial for the following individuals/roles:

  • IT professionals interested in big data and analytics
  • Data analysts seeking to enhance their skills
  • Professionals transitioning into the field of data science
  • Statisticians and mathematicians
  • Researchers and academics
  • Business intelligence analysts dealing with data for problem identification
  • Operations research analysts aiming for an industry-recognized certification.
  • Individuals preparing for the DS-110 (CDSP) exam.

Eligibility Criteria

Before taking this course, learners and professionals must have the following-

  • Having knowledge of fundamental data science concepts
  • Proficiency in programming (Python or R)
  • Familiarity with data manipulation and analysis tools
  • Experience working with SQL 
  • Basic understanding of statistics
  • Familiarity with machine learning 

Course Outline

Lesson 1: Addressing Business Issues with Data Science

  • Topic A: Initiate a Data Science Project 
  • Topic B: Formulate a Data Science Problem 

Lesson 2: Extracting, Transforming, and Loading Data

  • Topic A: Extract Data 
  • Topic B: Transform Data 
  • Topic C: Load Data 

Lesson 3: Analyzing Data

  • Topic A: Examine Data 
  • Topic B: Explore the Underlying Distribution of Data 
  • Topic C: Use Visualizations to Analyze Data 
  • Topic D: Preprocess Data 

Lesson 4: Designing a Machine Learning Approach

  • Topic A: Identify Machine Learning Concepts
  • Topic B: Test a Hypothesis

Lesson 5: Developing Classification Models

  • Topic A: Train and Tune Classification Models 
  • Topic B: Evaluate Classification Models 

Lesson 6: Developing Regression Models

  • Topic A: Train and Tune Regression Models 
  • Topic B: Evaluate Regression Models

Lesson 7: Developing Clustering Models

  • Topic A: Train and Tune Clustering Models 
  • Topic B: Evaluate Clustering Models 

Lesson 8: Finalizing a Data Science Project

  • Topic A: Communicate Results to Stakeholders 
  • Topic B: Demonstrate Models in a Web App 
  • Topic C: Implement and Test Production Pipelines

About The Certification

Certified Data Science Practitioner (CDSP)
Obtaining the Certified Data Science Practitioner (CDSP) certification can significantly boost career growth by providing learners with essential data analysis, machine learning, and data visualization skills. This credential enhances credibility, making professionals more attractive to employers and opening doors to a wide range of job opportunities in data-driven industries. CDSP certification demonstrates a commitment to excellence and proficiency in data science, leading to increased job prospects, higher earning potential, and opportunities for career advancement. CDSP is a valuable asset in accelerating professional growth and achieving success in the dynamic field of data science.

ABOUT THE EXAMINATION 

Exam Code
Exam Name
Exam Type
Exam Duration
Exam No. of Questions
Exam Passing Score
Exam Options
Training Course Required
 
DSP-110
Certified Data Science Practitioner (CDSP)
Multiple choice/ Scenario-based
120 minutes
100 (75 count towards final score)
70%
Pearson VUE test centers or online via Pearson OnVUE proctoring
Certified Data Science Practitioner course by CertNexus
 

Choose Your Preferred Mode

training option

Online Training

  • Support and assistance 24*7 to learn and resolve queries.
  • Engage in a comprehensive five days virtual training experience
  • Acquire access to premium-quality comprehensive training modules, course topics, and study tools.
  • Hybrid learning with a combination of instructor-led training and the flexibility of e-learning
Enroll Now 
training option

Corporate Training

  • Continual learning support with access to Vinsys labs and updated curriculum
  • Corporate entities are guaranteed an investment rate of return that is as high as feasible
  • Certified subject matter experts with more than two decades of experience
  • Ensure maximum ROI for corporates with Vinsys skill development programs.
     
Enroll Now 

FAQ’s

What is the total duration of the CDSP course? 

The total duration of the Certified Data Science Practitioner course is five days.

Does Vinsys offer any additional resources beyond the course?

In addition to the course material, you will receive practice examinations, feedback, and evaluation, along with reference materials and exam hints to aid your preparation.

Can a fresher join this course?

Before taking this course, you should have the fundamental knowledge of data science concepts with proficiency in programming (Python or R)

What is the CDSP course about?

This course covers different processes and techniques used in data science and how to implement other data models. It confirms proficiency in applying artificial intelligence and statistical models to analyze data and extract insights.
 

What are the related certifications to the Certified Data Science Practitioner Course?

The following are the related courses:
•    Certified Big Data Professional (CBDP)
•    Certified Artificial Intelligence Practitioner (CAIP)

Why should I choose Vinsys for the CDSP course?

Our expert-led training, supported by years of industry experience, has consistently provided top-tier corporate training and courses.

How is the exam for CDSP conducted?

The exam for this course is in a multiple-choice format and spans over 120 minutes. The exam code for this certification is DSP-110.
 

What are the minimum passing marks for this exam? 

To qualify for the certification, you must score at least 70% marks.

How will the online classes be conducted?

You have the flexibility to log in at the scheduled time for a live training session, where you can actively engage, learn, discuss, and share resources with both your peers and the instructors. 
 

When can I start training on the course?

You can select the date of your choice and, upon completing the formalities, opt for your preferred form of learning to commence your path to success
 

Why Vinsys

whyVinsys
Seasoned Instructors
Seasoned Instructors
Official Vendor Partnerships
Official Vendor Partnerships
Authorized Courseware
Authorized Courseware
3,000+ Courses & 2,000+ Modules
3,000+ Courses & 2,000+ Modules
In Synch with Tech-advancements
In Synch with Tech-advancements
Customizable Blended Learning Options
Customizable Blended Learning Options

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Reviews

Thank you, Vinsys, for an invaluable experience. The expert-led training provided a comprehensive understanding of data science concepts, from data collection to analysis and interpretation. The course material was well-structured, and the instructors were highly knowledgeable, offering practical insights and real-world examples.
Gautam DukeProject Manager
I appreciate the hands-on learning experience with Vinsys. The interactive sessions and practical exercises allowed me to apply the concepts learned in class to real datasets, enhancing my skills and confidence in data analysis. Additionally, the availability of practice examinations, feedback, and evaluation helped me gauge my progress and identify areas for improvement.
Kajal kapurSoftware Engineer

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