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