Data Science

Learn how to analyze and interpret data correctly.

The Master’s program in Data Science by College de Paris is a Minimum 12-month online professional program for students looking to start or advance a career in data science and offers strong preparation in statistical modeling, machine learning, optimization, management and analysis of massive data sets, and data acquisition. The program focuses on topics such as reproducible data analysis, collaborative problem solving, visualization and communication, and security and ethical issues that arise in data science.

Data Science and Artificial Intelligence have completely changed the world. Companies around the world are using artificial intelligence to eliminate repetitive tasks and improve the customer experience. Robots are taking the world by storm, continuously building an intelligence that rivals the human brain. Artificial intelligence and machine learning are the highest paying jobs in the world. Data science is an interdisciplinary field that uses methods and theories from mathematics, statistics, computer science, domain knowledge, and information science. It lies at the intersection of statistical methodology, computational science, and a wide range of application domains. According to recent estimates, more than 90% of his companies plan to use artificial intelligence in some way to develop or improve their products and services. These companies are looking for people who are proficient in data science and AI. Unfortunately, the industry faces a serious shortage of qualified employees to fill the void. Luckily, College de Paris decided to be part of the solution and started its Masters program in Data Science to help people use our services and earn their Data Science Certificate of Completion online.

The industry-relevant curriculum provides the skills to extract valuable insights from big data. This program provides expertise in statistical modeling, data management, machine learning, data visualization, software development, research design, data ethics, and user experience to meet the growing needs of industry, nonprofits, government agencies and other organizations. According to a McKinsey Global Institute report, data scientist is one of the best jobs in the United States, and there will be a huge demand for data scientists across industries over the next decade. This curriculum provides an opportunity to build knowledge and professional skills in a variety of data science areas that are in high demand in today's job market.

Why Data Science?

  • Data science helps businesses leverage social media content to capture real-time usage patterns of media content. It enables businesses to create targeted content, measure content performance, and recommend on-demand content. Retailers use data science to improve customer experience and customer retention.
  • Data science is widely used in banking and the financial sector for fraud detection and personalized financial advice.
  • Transportation agencies are using data science to improve transportation for their customers. For example, Transport for London maps customer journeys with personalized transport details and uses statistical data to manage unforeseen circumstances.
  • Construction companies use data science to make better decisions by tracking activities such as average time to complete tasks, material-based spend, and more.
  • Data science enables the interception and analysis of vast amounts of data from previously untapped manufacturing processes.
  • Data science allows you to analyze massive amounts of graphical, time-series, and geospatial data to gain insights. It is also useful for seismic interpretation and reservoir characterization.
  • In the healthcare industry, doctors are using data science to analyze data from wearable trackers to ensure patient health and make critical decisions. Data science also enables hospital administrators to reduce wait times and improve care.
  • Data science helps explore utility consumption in the energy and utilities sector. This research will allow us to scrutinize utility usage and improve consumer feedback.
  • Public sector data science applications include health-related research, financial market analysis, fraud detection, energy exploration, and environmental protection.

Learning Outcomes

  • Be well versed in analytics tools and technologies such as Python, Tableau, SQL
  • Build statistical models and understand their power and limitations
  • Apply industry-relevant machine learning techniques such as Regression, Predictive Modeling, Clustering, Time Series Forecasting, Classification, etc.
  • Acquire, clean, and manage data
  • Visualize data for exploration, analysis, and communication
  • Present yourself as an ideal candidate for analyst, data engineer, and data scientist roles within leading analytics companies Manage and analyze massive data sets
  • Assemble computational pipelines to support data science from widely available tools
  • Conduct data science activities aware of and according to policy, privacy, security and ethical considerations
  • Apply problem-solving strategies to open-ended questions
  • Be well versed in Deep learning, Natural Language Processing (NLP).

Why Collège de Paris?

Collège de Paris has been known for providing excellent education since 1949. It is accredited by organizations such as Campus France and the International Association of Language Centers. The university is committed to providing the best career opportunities for over 100,000 students coming from over 130 countries.

  • 10,000

    Students per Year

  • 25,000

    Continuing Education Trainees

  • 800+


  • 20

    Partner Universities

  • Top 500

    Best Global Universities

By the time you complete the academic requirements for your Data Science Masters’ degree, you will be able to:

Obtain, clean/process, and transform data

Analyze and interpret data using an ethically responsible approach

Use appropriate models of analysis, assess the quality of input, derive insight from results, and investigate potential issues

Apply computing theory, languages, and algorithms, as well as mathematical and statistical models, and the principles of optimization to appropriately formulate and use data analyses

Formulate and use appropriate models of data analysis to solve hidden solutions to business-related challenges

Interpret data findings effectively to any audience, orally, visually, and in written formats

Program Highlights

See which benefits you can derive from joining this program.

  • Online Program

    Minimum 12-month online program

    Industry Expert Mentor

    Highly Experienced Faculties

  • Collaborations

    Collège de Paris has designed agreements and conventions with academic institutions in France and abroad. This allows students to keep updated with the global learning pedagogy.

  • Dedicated Support Team for your Academic Journey

    Industry Experts Live Sessions

    Grievance Redressal System

    Dedicated Tech & Academic Support on how to leverage the platform features.

  • Become Job-ready

    Real-world case studies to build practical skills

    Hands-on exposure to analytics tools & techniques such as Python, Tableau, SQL

    Learn industry insights through multiple industry knowledge sessions

Program Curriculum

An overview of what you will learn from this program.

Python Programming

Database Management System

R Programming

Exploring Data Analysis

Machine Learning

Machine Learning Model Deployment

Artificial Intelligence

Data Visualization Using Tableau/Power BI

Capstone Projects

Test your skills and mettle with a capstone project.


Techniques used: Market Basket Analysis, RFM (Recency-Frequency Monetary) Analysis, Time Series Forecasting


Techniques used: Text Mining, Kmeans Clustering, Regression Trees, XGBoost, Neural Network

Web & Social Media

Techniques used: Topic Modeling using 9 Latent Dirichlet Allocation. K-Means & Hierarchical Clustering


Techniques used: Linear Discriminant Analysis, Logistic Regression, Neural Network, Boosting, Random Forest, CART

Supply Chain

Techniques used: Text Mining, Kmeans Clustering, Regression Trees, XGBoost, Neural Network


Techniques used: Logistic Regression, Random Tree, ADA Boost, Random Forest, KSVM


Techniques used: Market Basket Analysis, Brand Loyalty Analysis


Techniques used: NLP (Natural Language Processing), Vector Space Model, Latent Semantic Analysis

Entrepreneurship /Start Ups

Techniques used: Univariate and Bivariate Analysis, Multinomial Logistic Regression, Random Forest

Finance & Accounts

Techniques used: Conditional Inference Tree, Logistic Regression, CART and Random Forest

Why Careerera

Enrol with leading global online educational course provider.



Top Ranked Programs


Industry Experts


Expert Faculties


Data Science Batch Profile

Our students include freshers and experienced professionals from across industries, functions and backgrounds.


Learn from leading academicians and several experienced industry practitioners from top organizations.

Personalised workshops based on your proficiency level to help you get on par.

Mix of Live Classes & Recorded lectures for your convenience.

24*7 Student Support, Quick doubt resolution by industry experts

Alumni Highlights

  • 200+
    Global Companies
  • $122K PA
    Average CTC
  • $250K PA
    Highest CTC
  • 87%
    Average Salary Hike

Our student From

We have students from world leading companies.

Application Process

Enroll in the program with a simple online form.

Apply by filling a simple online application form

Admissions committee will review and shortlist.

Shortlisted candidates need to appear for an online aptitude test.

Screening call with Alumni/ Faculty

Sign Up

7 + 6 =


Find answers to all your queries and doubts here.

Q1 : How is the Master of Data Science different from the Master of Science in Business Analytics degree?

A : Data science and business analytics are unique disciplines, and the biggest difference is the scope of the problems covered. The science of data using algorithms, statistics, and technology is called data science. It provides actionable insights into a wide variety of structured and unstructured data that solve a broader perspective, such as customer behavior.

On the other hand, statistical analysis of mostly structured business data is called business analysis. We provide solutions to specific business problems and obstacles.

Q2 : What is the duration of course?

Q3 : What is the definition of Data Science? What makes it so important?

Q4 : Is Data Science a good Career choice?

Q5 : Which topics are covered in the course curriculum of the Masters in Data Science course?

Q6 : What are the skills required to start a job in the field of Data Science?

Q7 : Who is eligible for taking the Masters in Data Science course from College de Paris?