- Learn to represent and store data using Python data types and variables, and use conditionals and loops to control the flow of your programs.
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.
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.
Students per Year
Continuing Education Trainees
Best Global Universities
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
See which benefits you can derive from joining this program.
Minimum 12-month online program
Industry Expert Mentor
Highly Experienced Faculties
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.
Industry Experts Live Sessions
Grievance Redressal System
Dedicated Tech & Academic Support on how to leverage the platform features.
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
An overview of what you will learn from this program.
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
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
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
Techniques used: Univariate and Bivariate Analysis, Multinomial Logistic Regression, Random Forest
Techniques used: Conditional Inference Tree, Logistic Regression, CART and Random Forest
Enrol with leading global online educational course provider.
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
Enroll in the program with a simple online form.
Find answers to all your queries and doubts here.
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.
A : The Masters in Data Science course from College de Paris is a Minimum 12 month long online program.
A : Data is meaningless until it is transformed into valuable information. Data science mines large datasets of structured and unstructured data to identify hidden patterns and uncover actionable insights. The importance of data science lies in its myriad applications, from mundane activities like asking Siri or Alexa for recommendations to more complex applications like operating a self-driving car. The interdisciplinary fields of data science include computer science, statistics, inference, machine learning algorithms, predictive analytics, and emerging technologies.
A : Data science is in high demand across many industries, from IT, finance and e-commerce to manufacturing, healthcare and retail. The fastest growing job on LinkedIn, he is expected to create 11.5 million jobs by 2026. This makes data science a very lucrative career choice.Also, very few people actually have the skills needed to become a full data scientist. So while data scientists are in high demand, the supply of qualified talent is in short supply. As such, data scientists can demand as much salary as they want, and companies must meet that demand.
This data science master's program covers several topics related to data science. Some of them are: Regression, predictive modeling, clustering, time series forecasting, classification and more. I have an exercise where I need to structure a business problem using statistics and data modeling in an analytical framework. There are also topics on data cleansing, data transformation, deep learning, and natural language processing (NLP).
A : Skills required to get a data science job are: Python coding, Hadoop platform knowledge, SQL database/coding, machine learning and AI work domain specific knowledge, data visualization skills, statistics, multivariate calculus, linear algebra.
A : Companies looking to hire data scientists are looking for the following degrees -
- for recent graduates - B.Tech/M.Tech (any profession), BCA, MCA, or B.Sc ( Degree in Statistics or Mathematics) ), BA (Mathematics or Economics or Statistics), B.Com.
– For Professionals – 1+ years of professional experience in Python, R, SAS, Business Intelligence, Data Warehousing, SQL. Even if your work experience is not related to data analytics, you can switch to a data science career with one of the above degrees.
However, no technical or programming skills are required to enroll in the Master's Program in Data Science. Teach all modules from scratch.
They offer courses that combine practical experience with theoretical concepts.
Anyone who's wishing to improve their abilities and polish their resume can benefit from this Program.
It is comprehensive, skill-building courses that cover all you need to know to secure a good data scientist entry-level job.
This course combines in depth theoretical work with hands-on learning strategies to help students achieve efficiency in the most critical areas of data science roles available today.
This program is designed to help those who want to study and develop career relevant skills, tools and portfolio of projects in order to get a competitive edge during the entry level job search.
This program helped me to gain practical skills and apply them to real-world data science situations.
This curriculum considerably helped me to transition into a corporate career within the subject of data science because of this element of experiential earning.
The course aims to accelerate your career in the field of Data Science and provide you with the world-class skills required to become successful in this field. I would recommend this course to beginners and early professionals to learn essential data science skills.
It just teaches you the skills and information you need to know to understand what data science is and how it's done.