Overview of Certified Program in Data Science & Analytics

Data Scientists is a breed of data experts who have the technical skills to solve complex problems whereas analytics interpret data and turn it into information which can offer ways to improve a business. It’s no surprise many people are clamoring to find how to learn data science and analytics.

6-Month Online Program

Recorded Lectures & Group mentorship sessions

Dual Certifications - From UK and India

Virtual Internship @ Tata Consultancy Services

What you will learn from Data Science & Analytics?

  • It covers the four keys to data science field-1. Programming 2. Statistics 3. Data Science Models 4. Data Visualization
  • The course focuses on Python to build the data science programming. The raw data processing, analysis and visualization form a part of the preparatory model.
  • Statistics as required by the analyst is also covered during the course.
  • All the popular Data Science Algorithms are coursed to form a right blend of the knowledge acquired.
  • Able to create a business process with Data Science project.

Why join Data Science?

  • This course allows the students to get an in-depth knowledge by covering all the latest data science technology.
  • The increasing demand of data science professionals to manage the large data in organizations has created millions of job opportunities.
  • High salaries, nearly twice as that of average software engineer are another attractive option.
  • This course not only provides new career opportunities but also provides an add-on to your job profile in your current role.

Course Curriculum

  • Python for Data Science
  • Data Analytics Using Excel
  • Data Visualization using Tableau
  • Introduction to Statistics
  • Classification, Tabulation & Presentation of Data
  • Measures of Central Tendency & Dispersion
  • Simple Correlation & Regression
  • Testing of Hypothesis, Chi- Square Test, F-Distribution, ANOVA
  • Probability and Data Science
  • Linear Regression
  • Logistic Regression
  • Clustering
  • Principle Component Analysis (PCA)
  • Support Vector Machine (SVM)
  • Case Study

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