Introduction to Data Science in Marketing: An introductory module that covers the basics of data science, its applications in marketing, and the role of a data scientist in the field. Data Collection and Preparation: Learn how to gather and preprocess marketing data from various sources, including social media, websites, and customer databases.

This comprehensive data science course is designed to provide aspiring data scientists with a strong foundation in the field. The course covers a wide range of topics essential for data analysis and interpretation. It is suitable for individuals with a background in BE/BTech/MCA/MSc or related fields, aiming to excel in the world of data science. The program equips students with the knowledge and skills required to succeed in this data-driven era.


USD 38,500 /-
USD 44,000 /-

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Course Highlights

Industry-Recognized Certification: Upon successful completion, students receive a highly regarded certification, enhancing their career prospects.

Hands-on Projects: Engage in real-world data projects to apply theoretical knowledge to practical scenarios.

Expert-Led Training: Learn from experienced industry professionals and academic experts.

Comprehensive Syllabus: Explore a diverse range of subjects, including statistics, machine learning, data visualization, and more.

Access to Tools: Gain proficiency in industry-standard data science tools and software.

Mentorship and Support: Receive guidance and support throughout the course duration.

Career Services: Benefit from career support services, including job placement assistance.

Notable Alumni: Join a network of successful data science professionals who have completed this course.

Flexible Learning Options: Choose between online and in-person formats for added convenience.

Community and Networking: Connect with fellow students and build valuable professional relationships.



Completion of the Data Scientist-Marketing course with Skillfloor, you will be awarded a Certified Data Scientist-Marketing certification. This certification is specifically designed for individuals seeking to enhance their expertise in data science and its application in the field of marketing.

The Certified Data Scientist-Marketing program offered by Skillfloor equips professionals with the skills and knowledge necessary to analyze large volumes of data, extract valuable insights, and make data-driven decisions within the marketing domain. It covers essential topics such as statistical analysis, machine learning, and data-driven marketing strategies.


Top 10 Reasons For Choosing this Course

High Demand: Data scientists with marketing skills are in high demand as companies increasingly rely on data-driven marketing strategies.

Career Growth: Acquiring data science skills in marketing can lead to career advancement and higher salaries.

Data-Driven Decision Making: Learn to make marketing decisions backed by data and analytics, increasing the success of campaigns.

Personalization: Understand how data science can be used to personalize marketing efforts, improving customer engagement.

Competitive Edge: Gain a competitive advantage in the marketing job market with data science expertise.

Effective Marketing Campaigns: Discover how to optimize marketing campaigns, reducing costs and increasing ROI.

Market Segmentation: Learn to segment customers effectively, delivering tailored messages to specific audiences.

Analytical Skills: Develop strong analytical skills that are valuable in various industries beyond marketing.

Innovation: Contribute to marketing innovation by leveraging data for creative strategies.

Problem Solving: Acquire problem-solving skills to address complex marketing challenges using data-driven solutions.

Course Curriculum

  •  Concepts of data science
     Statistics and probability
     Data visualization
     Exploratory data analysis
     Hypothesis testing
     Regression analysis

  •  Data collection and storage
     Data cleaning
     Data transformation
     Feature engineering

  •  Supervised and unsupervised learning
     Classification and regression
     Model selection and evaluation

  •  Customer segmentation
     RFM analysis
     Market basket analysis
     Predictive modeling
     Campaign analysis

  •  Digital advertising
     Social media analytics
     Customer relationship management (CRM)
     Customer lifetime value (CLV)
     Marketing mix modeling

  •  Legal and ethical issues in data science
     Privacy concerns and regulations
     Bias and fairness in algorithms

  •  Applying data science techniques to a marketing problem
     Presenting findings and recommendations

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