Data Analytics – VIP Premium Batch

1.1 Excel formulas and functions

1.2 IF, SUMIF, COUNTIF, lookup functions, and logical functions

1.3 Sorting, filtering, and data validation

1.4 Pivot Tables and Pivot Charts

1.5 Conditional formatting and data cleaning

1.6 Advanced Excel reporting and dashboards

2.1 Database fundamentals and relational databases

2.2 SELECT, WHERE, ORDER BY, and DISTINCT

2.3 Aggregate functions and GROUP BY

2.4 Joins and subqueries

2.5 CASE statements and Common Table Expressions (CTEs)

2.6 Window functions and analytical queries

2.7 Data extraction and reporting using SQL

3.1 Descriptive statistics

3.2 Mean, median, mode, variance, and standard deviation

3.3 Probability fundamentals

3.4 Correlation and regression basics

3.5 Sampling and hypothesis testing

3.6 Interpreting statistical results for decision-making

4.1 Python fundamentals and data structures

4.2 NumPy for numerical computing

4.3 Pandas for data manipulation and analysis

4.4 Data cleaning and preprocessing

4.5 Exploratory Data Analysis (EDA)

4.6 Matplotlib and Seaborn for data visualization

4.7 Working with CSV, Excel, and other datasets

5.1 Importing and transforming data using Power Query

5.2 Data modeling and relationships

5.3 DAX formulas and calculated measures

5.4 Charts, KPIs, and interactive dashboards

5.5 Filters, slicers, and drill-through reports

5.6 Publishing and sharing reports

6.1 Connecting to different data sources

6.2 Charts, graphs, and data visualization

6.3 Calculated fields and filters

6.4 Interactive dashboards and stories

6.5 Visual analytics and business reporting

7.1 Handling missing and duplicate values

7.2 Identifying inconsistent data

7.3 Data transformation and formatting

7.4 Combining datasets from multiple sources

7.5 Preparing reliable datasets for analysis

8.1 Identifying patterns, trends, and outliers

8.2 KPI development and performance measurement

8.3 Business reporting and dashboard interpretation

8.4 Turning data into actionable insights

8.5 Communicating findings through reports and visualizations

9.1 Regression and predictive analytics basics

9.2 Time-series analysis fundamentals

9.3 Forecasting concepts

9.4 Introduction to machine learning for analytics

9.5 Understanding analytical models and their business applications

The course covers Microsoft Excel, SQL, Python, statistics, Power BI, Tableau, data cleaning, exploratory data analysis, business intelligence, and advanced analytics fundamentals.

Yes. Every student will be provided with an internship after successfully completing the 6-month training program.

Yes. The program includes practical exercises, assignments, datasets, case studies, and live projects to help students apply their data analytics skills.

This exclusive batch is limited to only 2 students to provide personalized guidance and individual attention.

The program is suitable for students, fresh graduates, and aspiring professionals who want to develop practical data analytics skills.

To enquire about enrollment, course details, or the curriculum, contact Khauriya Technologies at info@khauriyatechnologies.com or call 9993171557.