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Do you have a Bachelor's degree in Data Science? Are you missing out on your professional talent in a career in Data Science? Courses/certifications that can improve your skills and develop your intellectual abilities and potential in the field of Data Analytics Are you interested in record keeping? If the answer is yes, enroll in the Data Science Professional Certification today and take your knowledge and expertise to the next level.

The Data Science Professional Certification Course is designed to meet the evolving needs of data science professionals. If you're looking to become the best in data science with the skills that new global markets and industries are looking for, this certification is for you. With a practice-oriented training culture and professional guidance from experts, we are here for you.

The certification provides a space to engage in data-driven methods that contribute to the growth of organizations and their employees. Additionally, this course is designed to fill the shortage of trained professionals who are unable to properly operate systems in the industrial market. At Central Valley, we educate HR professionals who are ready to take the workforce by storm and create a better, more intelligent, and innovative world.

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The Time is Now


40
%
Analytics professionals in World have a work experience of less than 3 years.
61
%
Jobs are open for candidates with 0-5 years of experience.
3 M
The 2021 global estimate calls for 3 million job postings for analytics and data science roles.
36
%
The Global data science industry is growing at a healthy rate of 33.5 per cent CAGR.

Advanced Certification in Data Science - Key Highlights

  • Online Program 12-month online program along with Industry Internship and Online Lab Sessions & Highly Experienced Faculties.
  • Collaborations We aim to ensure our students are learning the skills needed within the industry so that they are ready and qualified for a professional role.
  • Become Job Ready Real-world case studies to build practical skills and Learn industry insights through multiple industry knowledge sessions
  • Job Interview Preparation Career guidance and mentorship by industry leaders and Access to opportunities with leading companies

Why choose a Data Science Professional Program?

Central Valley’s Data Science Professional is a program designed for fresh graduates and early career professionals looking to build their careers in data science & analytics. With a large number of job openings in the analytics and data science domain, Data Science Professional Prepares you with the right skills and knowledge needed to break into these roles. Central Valley University has collaborated with the industry to create a program that trains candidates specifically for roles such as Data Scientist, data analyst, data engineer, analytics engineer, and more by teaching relevant analytics techniques, tools, technologies, and hands-on applications through industry cases.

  • Build/grow your career in data science roles and companies.
  • Learn through live online sessions and hands-on learning.
  • Learn data science tools and technologies sought after by leading companies.

Admission Requirements

General Admission Requirements

  • Submission of a copy of valid government-issued picture identification.
  • Submission of a copy of an updated Resume.
  • Any document not in English must be accompanied by a certified translated copy.
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Admission Decisions & Process


We evaluate candidates based on their educational background, professional performance, consideration, and openness to applications. Ultimately, we are looking for ambitious young professionals with potential for leadership in our business.

  • Online Application

  • Online Assessment

  • Personal Interview

  • Entry Documents Verification

  • Final Committee Decision

Program Curriculum

Introduction to programming in Python

Introduction to DataBase Management System

Exploratory Data Analysis

Statistical Methods Of Decision Making

Machine Learning : Regression

Machine Learning : Classification

Unsupervised Learning : Clustering Techniques

Ensemble Techniques : Bagging, Boosting

Machine Learning Model Deployment Using Flask

Data Visualization Using Tableau

Data Visualization Using Google Data Studio