Data Science Course


The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges. Upon completing this course you will know how to clean and prepare your data for analysis, how to perform basic visualization of your data, how to model your data, how to curve-fit your data and finally, how to present your findings and wow the audience.


  • A person with diplomas in an analytical concentration, such as Computer Science, Math & Statistics, Management Information Systems, Economics, Engineering, and Hard Sciences.

  • The one who is curious about playing with data and have a passion for developing business decisions.

  • Information Architects who want to gain expertise in Predictive Analytics. Anyone who is familiar with the basic math and statistic concepts.

  • IT professionals and graduates who wish to get a career in data science and analytics.

  • Course Outline

    • Data Analytics & its Methodology

    • Fundamental of statistics

    • Data Visualization

    • Data Distribution & Correlation

    • Test of significance – Hypothesis testing, t-Test, ANOVA

    • Data Mining – Unsupervised & Supervised

    • Regression Analysis - Linear & Logistic

    • Cluster Analysis – Hierarchical & k-Means

    • Time series Analysi

    • Text Mining

    Enroll the course


    Devika Suresh

    The courses are really very helpful. The classes are easily follow-able and understandable. Each theory class is followed by a lab, also very helpful. Pretty good infrastructure.Would definitely recommend!.

    Romy Byju

    I did several courses at different institutions and I felt most comfortable because it has a well defined curriculum, good infrastructure, courseware and trainers of high quality.

    Maria Sajan

    It was my first experience with Recode AI and I really appreciate the infrastructure facilities as well as the friendly atmosphere we enjoyed there. The course we attended was very informatic . Looking forward for more.