Data Analysis

Course Outline

Data analytics is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

Basic Statistics for Data Analysis

(Inferential and Descriptive
Descriptive statistics
Concept of distribution (Skewness & Kurtosis)
Sampling & Sampling techniques
Hypothesis and types of hypothesis
Formulating hypothesis
p-value- confidence level, confidence interval
Statistical test (parametric test (t-test, ANOVA, chi-square test, etc) & non-parametric test (Mann-Whitney, Kruskal-Wallis, etc))
Interpreting test
Errors in Statistics

General outline
1. Introduction to data analysis and data science
2. Data collection
3. Data cleaning
4. Data analysis
5. Data visualization
6. Dashboard designing
7. Model building

Microsoft excel/ Spreadsheets
1. Introduction to the interface 2. Formulas and functions
3. Data cleaning
4. Conditional formatting
5. Pivot table
6. Data visualization 7. Dashboard building

Python
1. Variable naming and rules for naming variables
2. Type casting
3. Data Type conversion
4. List,tuples and dictionaries
5. Conditional Statement
6. Python loop
7. Function in python
8. File processing
9. Modules and libraries in python(numpy, pandas, seaborn,matplotlib)
10. Data analysis and visualization with numpy, pandas, seaborn and matplotlib)
11. Machine learning Model building using sklearn

Sql
1. Table creation in sql
2. Data importing using sql
3. Data cleaning using sql
4. Data exporting in sql to other visualization
tools

PowerBi/tableau
1.Introduction to interface
2.Data importing using powerbi/tableau
3.Data cleaning
4. Data Analysis
5. Data visualization
6. Dashboard building

Duration

Online 5 months. 2 times a week.
Weekends
Saturday and Sunday 7pm – 9pm
Weekdays Wednesdays and Fridays 7pm -9pm.

On-site 4 months. 2 times a week
Weekend : Saturday 9 – 2pm
Sunday 2 – 6pm

Onsite Price – 200,000

Weekdays :
Wednesdays 2pm – 6pm
Fridays 9am – 2pm