ADVANCED DATA ANALYTICS

(Self Paced Course )

(14) Courses
Recording	CV Prepration

₹84,000 82.28% OFF

₹15,000/- Including 18% GST

Description Course Content How To Use

Description:

The Advanced Data Analytics program prepares candidates for high-demand careers by mastering data analysis, visualization, and machine learning. With these skills, you'll drive data-driven decisions, increase employability in top industries, and unlock growth opportunities in the fast-evolving world of analytics. .

Key Highlights:

High-Demand Skills: Master advanced tools like Python, SQL, and machine learning to stand out in the competitive job market.
Lucrative Opportunities: Unlock high-paying roles in data science, business intelligence, and analytics across top industries.
Career Growth: Gain expertise in data-driven decision-making, increasing your employability and potential for leadership positions.
Hands-On Learning: Practical projects and real-world case studies ensure you’re job-ready from day one.
Industry-Relevant Curriculum: Stay ahead with the latest trends and techniques in data analysis, enhancing your long-term career prospects.

What you will learn:

SQL Queries [Basic To Advanced]
ETL Datawarehouse
Power BI
Tableau
Advanced Excel
Statistics And Probability
Python
Business Problem Solving, Insights and Storytelling
BigData Analytics
AWS Cloud Analytics
Azure Cloud Analytics
Business Case Studies
CV Preparation
Interview Preparation (25 Interviews)

SQL Queries [Basic To Advanced}

	Topic	Duration
1	Introduction to Database & Importance of Database	10 Minutes
2	How to Download & Install Database	10 Minutes
3	How to Launch SSMS & Connect Database	5 Minutes
4	Create Database	5 Minutes
5	Database Objects and Data Types	30 Minutes
6	Data Handlings as per Data Type	25 Minutes
7	About Table & Create Table	15 Minutes
8	Insert Data In Table with Both Syntax	30 Minutes
9	Select Statement with All Columns and Specific Columns	30 Minutes
10	Practice with Update & Delete	30 Minutes
11	Top & Distinct Keywords	30 Minutes
12	Order By & Order by with Multiple Columns	30 Minutes
13	Practice with Where Clause	15 Minutes
14	Practice with AND, OR & BETWEEN	45 Minutes
15	Practice with LIKE	20 Minutes
16	Practice with NOT, IN & Alias	30 Minutes
17	Wildcard Characters	30 Minutes
18	Working with	60 Minutes
19	Aggregate Functions	30 Minutes
20	About Group By and Why We Use It?	30 Minutes
21	Practice with Group By	150 Minutes
22	Practice with Group By with Multiple Columns	60 Minutes
23	Unions and Realtime Use of Unions	150 Minutes
24	About Joins & Type of Joins	25 Minutes
25	Inner Join and Realtime Use of Inner Join	60 Minutes
26	Left Join and Realtime Use of Left Join	60 Minutes
27	Right Join and Realtime Use of Right Join	60 Minutes
28	Full Join and Realtime Use of Full Join	60 Minutes
29	Cross Join and Realtime Use of Cross Join	60 Minutes
30	Self Join and Realtime Use of Self Join	90 Minutes
21	Practice with Group By	150 Minutes
22	Practice with Group By with Multiple Columns	60 Minutes
23	Unions and Realtime Use of Unions	150 Minutes
24	About Joins & Type of Joins	25 Minutes
25	Inner Join and Realtime Use of Inner Join	60 Minutes
26	Left Join and Realtime Use of Left Join	60 Minutes
27	Right Join and Realtime Use of Right Join	60 Minutes
28	Full Join and Realtime Use of Full Join	60 Minutes
29	Cross Join and Realtime Use of Cross Join	60 Minutes
30	Self Join and Realtime Use of Self Join	90 Minutes
31	Practice with Joins with 3 Tables	60 Minutes
32	Practice with Joins with 4 Tables	60 Minutes
33	About Constraints, Type of Constraints	10 Minutes
34	Constraints in Detail with Realtime Use	150 Minutes
35	Operations on a Table	60 Minutes
36	Date Functions and Realtime Use	120 Minutes
37	Handling Nulls and Practice with Example	60 Minutes
38	System Functions and Realtime Use	90 Minutes
39	What is Case Statement and Why We Use It	15 Minutes
40	Practice with Case Statement with Multiple Examples	120 Minutes
41	Sub Query & Co-related Sub Query	100 Minutes
42	Get nth Position Record Using Sub Query	60 Minutes
43	Exist & Not Exist and Its Realtime Use	60 Minutes
44	Common Table Expression	120 Minutes
45	Find Duplicate Records & Find Unique Records	30 Minutes
46	Find nth Position Records	30 Minutes
47	Find Latest Records, Find Oldest Records & Remove Duplicate Records	90 Minutes
48	Working with Row_Number(), Rank() & Dense Rank() Functions	60 Minutes
49	What is Index and Why We Use It	20 Minutes
50	Type of Index, Create Index, Drop Index, Realtime Use of Index	120 Minutes
51	About Views, Create View and Practice with It	95 Minutes
52	About Store Procedures	10 Minutes
53	Type of Store Procedures and Realtime Use of These	120 Minutes
54	About Functions, Type of Functions & Practice with Functions	90 Minutes
55	About Trigger, Realtime Use of Trigger and Practice with Trigger	60 Minutes
56	Practice on SQL Query Preparation on Business Scenarios-1	60 Minutes
57	Practice on SQL Query Preparation on Business Scenarios-2	60 Minutes
58	Practice on SQL Query Preparation on Business Scenarios-3	60 Minutes
59	Practice on SQL Query Preparation on Business Scenarios-4	60 Minutes
60	Practice on SQL Query Preparation on Business Scenarios-5	60 Minutes
61	Assignment #1
62	Assignment #2
63	Assignment #3
64	Assignment #4
65	Assignment #5

ETL Datawarehouse

	Topic	Duration
1	What is ETL	10 Minutes
2	Importance of ETL	15 Minutes
3	What is Datawarehouse	15 Minutes
4	Importance of Datawarehouse	15 Minutes
5	ETL Architecture	20 Minutes
6	Transformation, Lookup	25 Minutes
7	Duplicate Data, Data Cleaning	60 Minutes
8	Source, Staging, Target	15 Minutes
9	Type of Schemas in Datawarehouse	10 Minutes
10	Star Schema	15 Minutes
11	Snowflake Schema	15 Minutes
12	About DIM Tables and Types	15 Minutes
13	SCD Type 1	15 Minutes
14	SCD Type 2	15 Minutes
15	SCD Type 3	15 Minutes
16	SCD Type 4	15 Minutes
17	SCD Type 6	15 Minutes
18	About FACTs and Type of FACTs	15 Minutes
19	Additive Fact	15 Minutes
20	Semi Additive Fact	15 Minutes
21	Non Additive Fact	15 Minutes
22	Factless Fact	15 Minutes
23	End to End Practice at Project	120 Minutes
	Assignment #1
	Assignment #2
	Assignment #3

Power BI

	Topic	Duration
	Module 1: Introduction to Power BI (Basics)
1	Session-1: Overview of Business Intelligence and Power BI	15 Minutes
2	Topic-1: What is Power BI and why use it?
3	Topic-2: Power BI ecosystem (Desktop, Service, Mobile, Report Server)
4	Session-2: Installing Power BI Desktop	15 Minutes
5	Topic-1: System requirements
6	Topic-2: Initial setup and configurations
7	Session-3: Understanding the Power BI Interface	15 Minutes
8	Topic-1: Ribbon, Panes, and Views
9	Topic-2: Different types of views: Report, Data, and Model view
10	Session-4: Connecting to Data Sources	60 Minutes
11	Topic-1: Importing data from Excel, CSV, and databases
12	Topic-2: Connecting to online services (SharePoint, Azure, etc.)
13	Session-5: Data Transformation with Power Query	45 Minutes
14	Topic-1: Introduction to Power Query Editor
15	Topic-2: Data cleaning and shaping (removing columns, renaming, filtering, etc.)
16	Session-6: Merging and Appending Data	30 Minutes
17	Topic-1: Combining multiple data sources
18	Topic-2: Using “Append Queries” and “Merge Queries”
19	Session-7: Data Modeling Basics	30 Minutes
20	Topic-1: Understanding relationships between tables
21	Topic-2: Cardinality and cross-filter direction
22	Session-8: Creating Basic Visualizations	45 Minutes
23	Topic-1: Creating charts (bar, line, pie, etc.)
24	Topic-2: Tables and Matrix visuals
Module 2: Power BI Intermediate Topics
25	Session-9: Calculated Columns and Measures	60 Minutes
26	Topic-1: Creating calculated columns
27	Topic-2: Introduction to DAX (Data Analysis Expressions)
28	Topic-3: Basic measures (sum, average, etc.)
29	Session-10: Advanced Data Transformations in Power Query	60 Minutes
30	Topic-1: Advanced transformations (pivot/unpivot, custom columns)
31	Topic-2: Grouping data and aggregating
32	Session-11: Time Intelligence in Power BI	30 Minutes
33	Topic-1: Using DAX for time-based calculations (YTD, MTD, etc.)
34	Topic-2: Working with date tables
35	Session-12: Hierarchies and Drill-downs	20 Minutes
36	Topic-1: Creating and using hierarchies (time, geography, etc.)
37	Topic-2: Enabling drill-down and drill-through capabilities in reports
38	Session-13: Advanced Visualizations	40 Minutes
39	Topic-1: Customizing visualizations
40	Topic-2: Using slicers, filters, and bookmarks
41	Session-14: Formatting and Themes	30 Minutes
42	Topic-1: Custom formatting options for visuals and reports
43	Topic-2: Applying custom report themes
44	Session-15: Introduction to Power BI Service	15 Minutes
45	Topic-1: Publishing reports to Power BI Service
46	Topic-2: Creating and sharing dashboards in Power BI Service
47	Session-16: Row-Level Security (RLS)	20 Minutes
48	Topic-1: Setting up row-level security
49	Topic-2: Managing user roles and permissions
50	Session-17: Working with Power BI Mobile App	25 Minutes
51	Topic-1: Optimizing reports for mobile viewing
52	Topic-2: Navigation and interaction in the mobile app
Module 3: Advanced Power BI
53	Session-18: Advanced DAX Functions	30 Minutes
54	Topic-1: CALCULATE, ALL, RELATED, and other advanced DAX functions
55	Topic-2: Context in DAX (Row and Filter context)
56	Session-19: Using Parameters and What-if Analysis	15 Minutes
57	Topic-1: Creating and using parameters in reports
58	Topic-2: Implementing What-if scenarios
59	Session-20: Advanced Data Modeling Techniques	60 Minutes
60	Topic-1: Star schema vs Snowflake schema
61	Topic-2: Fact and dimension tables
62	Session-21: Advanced Analytics in Power BI	20 Minutes
63	Topic-1: Forecasting and clustering
64	Topic-2: Using quick insights for advanced analytics
65	Session-22: Power BI Performance Optimization	25 Minutes
66	Topic-1: Improving report performance
67	Topic-2: Best practices for data modeling
68	Session-23: Power BI Dataflows	15 Minutes
69	Topic-1: Understanding and creating dataflows
70	Topic-2: Using dataflows for ETL processes
71	Session-24: Paginated Reports in Power BI	20 Minutes
72	Topic-1: Creating and deploying paginated reports
73	Topic-2: Differences between paginated and regular reports
74	Session-25: Power BI and AI Integration	25 Minutes
75	Topic-1: Using AI visuals (Key Influencers, Decomposition Tree)
76	Topic-2: Integration with Azure Machine Learning
77	Session-26: Integrating Power BI with Other Tools	60 Minutes
78	Topic-1: Power BI and Excel integration
79	Topic-2: Power BI and SharePoint/Teams integration
80	Session-27: Power BI Gateways	30 Minutes
81	Topic-1: Setting up an on-premise data gateway
82	Topic-2: Scheduling data refreshes with gateways
Module 4: Power BI Expert Topics
83	Session-28: Custom Visuals Development	30 Minutes
84	Topic-1: Importing and using custom visuals from the marketplace
85	Topic-2: Developing custom visuals using Power BI SDK
86	Session-29: Power BI API and Embedding	60 Minutes
87	Topic-1: Introduction to Power BI API
88	Topic-2: Embedding Power BI reports into applications (web, desktop)
89	Session-30: Advanced Power BI Service Features	30 Minutes
90	Topic-1: Data lineage and impact analysis
91	Topic-2: Advanced sharing and collaboration in workspaces
92	Session-31: Advanced Power Query – M Language	60 Minutes
93	Topic-1: Introduction to M Language
94	Topic-2: Writing custom M scripts for data transformation
95	Session-32: Deployment Pipelines	30 Minutes
96	Topic-1: Creating deployment pipelines for Dev, Test, Prod environments
97	Session-33: Power BI Administration	30 Minutes
98	Topic-1: Admin roles and permissions in Power BI

Tableau

	Topic	Duration
	Module 1: Basics of Tableau
1	Session 1: Introduction to Tableau	60 Minutes
2	Topic-1: What is Tableau and its importance
3	Topic-2: Tableau interface and workspace
4	Topic-3: Different Tableau products (Desktop, Public, Online, Server, Reader)
5	Session 2: Data Connection	60 Minutes
6	Topic-1: Connecting to different data sources (Excel, SQL Server, CSV, etc.)
7	Topic-2: Importing data and managing connections
8	Topic-3: Live vs Extract connection
9	Session 3: Data Preparation	90 Minutes
10	Topic-1: Data cleaning, filtering, and sorting
11	Topic-2: Handling null values
12	Topic-3: Data types and roles (Dimension, Measure)
13	Topic-4: Creating hierarchies, groups, sets, and bins
14	Topic-5: Joins, blends, and unions
Module 2: Basic Visualization Techniques
15	Session 4: Simple Charts	60 Minutes
16	Topic-1: Bar chart, Line chart, Pie chart, Scatter plot
17	Topic-2: Creating and modifying charts
18	Topic-3: Dual-axis and combined charts
19	Session 5: Filtering and Sorting	45 Minutes
20	Topic-1: Applying filters (dimension filters, measure filters)
21	Topic-2: Sorting data in visualizations
22	Topic-3: Interactive filters for users
23	Session 6: Calculated Fields	60 Minutes
24	Topic-1: Basic arithmetic and logical calculations
25	Topic-2: String and date calculations
26	Topic-3: Introduction to Tableau’s calculation syntax
Module 3: Intermediate Visualization
27	Session 7: Table Calculations	60 Minutes
28	Topic-1: Basic table calculations (Running Total, Percent of Total)
29	Topic-2: Quick Table Calculations (Moving Average, YTD growth)
30	Session 8: Mapping	60 Minutes
31	Topic-1: Creating maps with geographical data
32	Topic-2: Customizing maps (adding layers, map styles)
33	Topic-3: Heat maps, density maps, symbol maps
34	Session 9: Dashboards	120 Minutes
35	Topic-1: Building dashboards with multiple visualizations
36	Topic-2: Creating interactive dashboards (actions, filters)
37	Topic-3: Using layout containers for responsive design
38	Topic-4: Best practices for effective dashboard design
39	Session 10: Storytelling	60 Minutes
40	Topic-1: Creating and organizing stories
41	Topic-2: Adding captions, annotations, and filters to stories
42	Topic-3: Story best practices for business reporting
Module 4: Advanced Tableau
43	Session 11: Advanced Calculations	60 Minutes
44	Topic-1: LOD Expressions (Fixed, Include, Exclude)
45	Topic-2: Advanced table calculations (Rank, Index, Window Functions)
46	Topic-3: Conditional and nested calculations
47	Session 12: Advanced Visualizations	60 Minutes
48	Topic-1: Bullet charts, Box plots, Waterfall charts, Gantt charts
49	Topic-2: Motion charts, Sparklines, Word clouds
50	Topic-3: Advanced mapping techniques (Path maps, Spider maps)
51	Session 13: Parameters	60 Minutes
52	Topic-1: Creating and using parameters in calculations
53	Topic-2: Parameter controls in dashboards
54	Topic-3: Dynamic visualizations using parameters
55	Session 14: Data Modeling	60 Minutes
56	Topic-1: Relationships in Tableau (physical layer vs logical layer)
57	Topic-2: Performance optimization (Extracts, Aggregations, Context Filters)
Module 5: Data Interaction and Integration
58	Session 15: Data Blending	60 Minutes
59	Topic-1: Combining data from multiple sources
60	Topic-2: Managing data relationships
61	Topic-3: Handling blended data issues
62	Session 16: Tableau Prep	60 Minutes
63	Topic-1: Introduction to Tableau Prep for data preparation
64	Topic-2: Workflow creation in Tableau Prep
65	Topic-3: Cleaning, shaping, and transforming data with Prep
66	Session 17: Tableau Server & Tableau Online	60 Minutes
67	Topic-1: Publishing workbooks to Tableau Server/Tableau Online
68	Topic-2: Managing permissions and user roles
69	Topic-3: Scheduling data refreshes and alerts
Module 6: Best Practices and Performance Tuning
70	Session 18: Performance Optimization	15 Minutes
71	Topic-1: Using Extracts vs Live Connections
72	Topic-2: Optimization techniques (minimize calculations, data extracts, filtering)
73	Topic-3: Understanding Tableau’s Performance Recording tool
74	Session 19: Design Best Practices	30 Minutes
75	Topic-1: Choosing the right chart for the right data
76	Topic-2: Building user-friendly dashboards
77	Topic-3: Using color, text, and layout effectively
Project
78	Practice on Realtime Project-1	90 Minutes
79	Practice on Realtime Project-2	90 Minutes
80	Practice on Realtime Project-3	90 Minutes
81	Practice on Realtime Project-4	90 Minutes
82	Practice on Realtime Project-5	90 Minutes

Advanced Excel

	Topic	Duration
	Module 1: Basics of Excel
1	Session 1: Introduction to Excel (Basics)	60 Minutes
2	Understanding the Excel Interface
3	Workbook, Worksheets, Rows, Columns, and Cells
4	Data Entry, Editing, and Formatting
5	Keyboard Shortcuts for Efficiency
6	Saving, Opening, and Printing Excel Files
7	Session 2: Formatting Excel Worksheets	60 Minutes
8	Cell Formatting (Fonts, Colors, Borders, Alignment)
9	Conditional Formatting (Color Scales, Data Bars, Custom Rules)
10	Applying and Customizing Themes
11	Working with Tables (Table Styles, Quick Formatting)
12	Session 3: Data Manipulation & Organization	60 Minutes
13	Sorting and Filtering Data
14	Data Validation (Creating Drop-Down Lists)
15	Removing Duplicates
16	Grouping and Subtotaling Data
17	Custom Number Formatting
18	Session 4: Functions and Formulas (Intermediate)	120 Minutes
19	Mathematical and Statistical Functions (SUM, AVERAGE, COUNT, COUNTA, etc.)
20	Logical Functions (IF, AND, OR, NOT)
21	Lookup and Reference Functions (VLOOKUP, HLOOKUP, INDEX, MATCH)
22	Text Functions (CONCATENATE, LEFT, RIGHT, MID, TRIM, LEN)
23	Date and Time Functions (TODAY, NOW, DATEDIF, EDATE)
24	Session 5: PivotTables and PivotCharts	120 Minutes
25	Creating and Customizing PivotTables
26	Using Filters, Slicers, and Timelines in PivotTables
27	Grouping Data in PivotTables
28	PivotCharts: Visualization of PivotTable Data
29	Calculated Fields in PivotTables
30	Session 6: Data Visualization with Excel	120 Minutes
31	Creating and Customizing Charts (Bar, Line, Pie, Combo)
32	Sparklines and Mini Charts
33	Creating Heat Maps and Data Bars
34	Advanced Chart Techniques (Dual-Axis Charts, Customizing Labels)
35	Dynamic Charts Using Data Validation Lists
36	Session 7: Advanced Formulas and Functions	120 Minutes
37	Advanced Lookup (XLOOKUP, INDIRECT, OFFSET)
38	Array Formulas and Dynamic Arrays (FILTER, SORT, UNIQUE)
39	Financial Functions (NPV, IRR, PMT)
40	Error Handling Functions (IFERROR, ISERROR, IFNA)
41	Session 8: Data Analysis Tools	60 Minutes
42	What-If Analysis (Goal Seek, Data Tables, Scenario Manager)
43	Solver Tool (Optimization)
44	Descriptive Statistics Using Data Analysis Toolpak
45	Using Power Query for Data Import and Transformation
46	Session 9: Macros and Automation	120 Minutes
47	Introduction to Macros and VBA (Recording Macros)
48	Editing and Customizing Macros (Basic VBA Code)
49	Creating Buttons and Assigning Macros
50	Automating Repetitive Tasks with Macros
51	Session 10: Collaboration and Sharing	60 Minutes
52	Protecting Worksheets and Workbooks (Password Protection)
53	Sharing and Collaborating on Excel Workbooks
54	Track Changes and Version History
55	Co-authoring in Excel
56	Session 11: PowerPivot and Power BI Integration	60 Minutes
57	Introduction to PowerPivot
58	Creating Data Models with PowerPivot
59	DAX (Data Analysis Expressions) Functions
60	Excel to Power BI Integration
Project
61	Practice on Realtime Project-1	90 Minutes
62	Practice on Realtime Project-2	90 Minutes
63	Practice on Realtime Project-3	90 Minutes
64	Practice on Realtime Project-4	90 Minutes
65	Practice on Realtime Project-5	90 Minutes

Statistics & Probablity

	Topic	Duration
	Module 1: Introduction to Statistics and Probability
1	Session-1: Descriptive Statistics	35 Minutes
2	Types of Data: Qualitative vs. Quantitative
3	Measures of Central Tendency (Mean, Median, Mode)
4	Measures of Dispersion (Variance, Standard Deviation, Range, Interquartile Range)
5	Shape of Distribution: Skewness, Kurtosis
6	Visualizations: Histogram, Boxplot, Bar chart
7	Session-2: Introduction to Probability	20 Minutes
8	Basics of Probability
9	Probability Rules (Addition and Multiplication Rules)
10	Conditional Probability and Bayes’ Theorem
11	Independence vs. Dependence
12	Session-3: Combinatorics	25 Minutes
13	Permutations and Combinations
14	Applications in Probability
Module 2: Probability Distributions
15	Session-4: Discrete Probability Distributions	30 Minutes
16	Bernoulli Distribution
17	Binomial Distribution
18	Poisson Distribution
19	Geometric Distribution
20	Session-5: Continuous Probability Distributions	20 Minutes
21	Normal Distribution (Properties and Empirical Rule)
22	Uniform Distribution
23	Exponential Distribution
24	Session-6: Sampling Distributions	25 Minutes
25	Law of Large Numbers
26	Central Limit Theorem
27	Understanding the Concept of Sampling Distribution of a Statistic (Mean, Proportion)
Module 3: Inferential Statistics
28	Session-7: Point Estimation and Confidence Intervals	20 Minutes
29	Estimating Population Parameters
30	Confidence Intervals for Means and Proportions
31	Session-8: Hypothesis Testing	60 Minutes
32	Null and Alternative Hypotheses
33	Type I and Type II Errors
34	p-Values and Significance Level (α)
35	Z-test, T-test (1-sample, 2-sample, Paired t-tests)
36	Chi-Square Test for Independence
37	ANOVA (Analysis of Variance)
38	Session-9: Non-Parametric Tests	15 Minutes
39	Wilcoxon Rank-Sum Test
40	Kruskal-Wallis Test
41	Mann-Whitney U Test
Module 4: Advanced Probability and Statistics
42	Session-10: Bayesian Statistics	30 Minutes
43	Introduction to Bayesian Thinking
44	Bayesian Inference
45	Prior, Likelihood, Posterior
46	Session-11: Markov Chains	30 Minutes
47	Introduction to Markov Processes
48	Transition Matrix and State Probability
49	Applications in Time Series and Random Processes
Module 5: Regression and Predictive Modeling
54	Session-13: Simple Linear Regression	30 Minutes
55	Line of Best Fit
56	Coefficients and Interpretation
57	Residual Analysis and Assumptions of Regression
58	Session-14: Multiple Linear Regression	30 Minutes
59	Multiple Predictors
60	Variance Inflation Factor (VIF) and Multicollinearity
61	Model Evaluation: R-squared, Adjusted R-squared, AIC/BIC
62	Session-15: Logistic Regression	30 Minutes
63	Odds Ratio and Log Odds
64	Maximum Likelihood Estimation (MLE)
65	ROC Curve, AUC, Precision-Recall
Module 6: Time Series Analysis
66	Session-16: Introduction to Time Series Data	30 Minutes
67	Components of Time Series: Trend, Seasonality, Noise
68	Stationarity and Differencing
69	Session-17: Time Series Forecasting Models	30 Minutes
70	Moving Averages and Exponential Smoothing
71	ARIMA (AutoRegressive Integrated Moving Average)
72	Seasonal Decomposition of Time Series (STL)
73	Time Series in Python
74	Plotting and Decomposing Time Series Data
75	Building ARIMA Models and Forecasting
Module 7: Applied Probability in Machine Learning
76	Session-18: Decision Trees and Random Forests	30 Minutes
77	Gini Index and Entropy
78	Understanding Feature Importance
79	Session-19: Naive Bayes Classifier	30 Minutes
80	Theoretical Foundation
81	Multinomial, Gaussian, and Bernoulli Naive Bayes
82	Session-20: Probabilistic Graphical Models	30 Minutes
83	Introduction to Bayesian Networks
84	Inference and Prediction using PGMs
Module 8: Data Testing & Quality Assurance with Statistics
85	Session-21: AB Testing	30 Minutes
86	Experimental Design
87	Hypothesis Testing for Business Decisions
88	Session-22: Data Validation Techniques	30 Minutes
89	Detecting Anomalies in Data
90	Statistical Quality Control
91	Application of Control Charts
92	Session-23: Statistical Modeling for ETL Processes	30 Minutes
93	Outlier Detection
94	Data Profiling using Statistical Methods

Python

	Topic	Duration
1	Module 1: Introduction to Python for Data Analytics
2	Session-1: Installation: Install Python, Jupyter Notebook, and essential libraries	40 Minutes
3	Session-2: Basic Python Syntax: Variables, data types, conditionals, loops, functions	120 Minutes
4	Module 2: Data Handling with Pandas
5	Session-3: Basic Operation - Loading data from CSV, Excel, databases	60 Minutes
6	Session-4: Basic Operation - Inspecting the dataset: df.head(), df.info(), df.describe()	60 Minutes
7	Session-5: Basic Operation - Selecting and filtering data	30 Minutes
8	Session-6: Basic Operation - Adding and removing columns: df['new_col'] = df['old_col'] * 2, df.drop('col', axis=1)	30 Minutes
9	Session-7: Data Cleaning - Handling missing data: df.fillna(), df.dropna()	60 Minutes
10	Session-8: Data Cleaning - String operations: df['column'].str.lower(), df['column'].str.replace()	60 Minutes
11	Module 3: Data Manipulation
12	Session-9: Grouping and Aggregation: groupby(), agg(), sum(), mean()	60 Minutes
13	Session-10: Merging and Joining: Combining data with merge(), concat()	60 Minutes
14	Session-11: Pivot Tables: Creating pivot tables	30 Minutes
15	Module 4: Exploratory Data Analysis (EDA)
16	Session-12: Visualization with Matplotlib and Seaborn: Basic plotting	45 Minutes
17	Session-13: Visualization with Matplotlib and Seaborn: Scatter plots, bar charts, histograms	60 Minutes
18	Session-14: Summary Statistics: Mean, median, mode	60 Minutes
19	Session-15: Summary Statistics: Correlation matrix	30 Minutes
20	Module 5: Advanced Data Manipulation
21	Session-16: Multi-indexing: Handling multi-level indexing in dataframes	45 Minutes
22	Session-17: Reshaping Data: Using melt() and stack() to reshape datasets	60 Minutes
23	Module 6: Feature Engineering
24	Session-18: Dealing with Date and Time Data: Parsing dates, extracting year, month, day	90 Minutes
25	Session-19: Dealing with Date and Time Data: Handling time series data	60 Minutes
26	Session-20: Handling Categorical Data: Encoding categorical variables using pd.get_dummies()	85 Minutes
27	Module 7: Introduction to Machine Learning
28	Session-21: Supervised Learning: Linear Regression	60 Minutes
29	Session-22: Supervised Learning: Classification with Logistic Regression, Decision Trees	60 Minutes
30	Session-23: Unsupervised Learning: K-means Clustering	60 Minutes
31	Module 8: Model Evaluation
32	Session-24: Train/Test Split: Splitting data into training and test sets	60 Minutes
33	Session-25: Model Metrics: Evaluating models using accuracy, precision, recall, F1-score	60 Minutes
34	Module 9: Data Pipelines and Automation
35	Session-26: Building Pipelines with Sklearn: Automating data transformation and model fitting	60 Minutes
36	Module 10: Working with Large Datasets
37	Session-27: Optimizing Pandas for Large Datasets: Loading chunks, working with dask or modin	60 Minutes
38	End to End Practice at Realtime Project	120 Minutes

Business Problem Solving Inseights & Storytelling

	Topic	Duration
	Understanding the Business Problem
1	Gathering Requirements	60 Minutes
2	Framing the Problem
3	Identifying Metrics
	Data Collection and Exploration
4	Clean the Data	60 Minutes
5	Explore the Data
	Generating Insights
6	Identifying Trends
7	Finding Correlations
8	Performing Analysis
	Storytelling and Presenting Insights
9	Create a Narrative	60 Minutes
10	Use Visuals
11	Tailor the Presentation
	Driving Actionable Recommendations
12	Strategic Actions	60 Minutes
13	Measurable Impact
	Continuous Monitoring and Feedback
14	Track Key Metrics	60 Minutes
15	Iterate
	Case Study: Solving Low Customer Retention
16	Problem	120 Minutes
17	Data Collection
18	Exploration
19	Insight
20	Recommendation
21	Outcome Monitoring

BigData Anaytics

	Topic	Duration
1	Introduction to Big Data Analytics	120 Minutes
2	Big Data Ecosystem	60 Minutes
3	ETL (Extract, Transform, Load) in Big Data	120 Minutes
4	Data Analysis Techniques	90 Minutes
5	Big Data Analytics with SQL	135 Minutes
6	Real-Time Data Processing with Apache Kafka	90 Minutes
7	Visualization of Big Data	60 Minutes
8	Machine Learning on Big Data	60 Minutes
9	Final Project: Analyzing a Big Dataset	60 Minutes

AWS Cloud Analytics

	Topic	Duration
1	Introduction to AWS Cloud Analytics	120 Minutes
2	Amazon Redshift	90 Minutes
3	Amazon Athena	120 Minutes
4	AWS Glue	120 Minutes
5	Amazon Kinesis	120 Minutes
6	Amazon QuickSight	120 Minutes
7	Amazon EMR (Elastic MapReduce)	120 Minutes
8	End to End Practice	120 Minutes

Azure Cloud Analytics

	Topic	Duration
1	Module 1: Introduction to Azure Cloud Analytics
2	Session-1 - Azure Data Lake Storage (ADLS)	60 Minutes
3	Session-2 - Azure Synapse Analytics	60 Minutes
4	Session-3 - Azure Databricks	60 Minutes
5	Session-4 - Azure Machine Learning	60 Minutes
6	Session-5 - Azure Stream Analytics	60 Minutes
7	Module 2: Setting up Azure Data Lake Storage (ADLS)
8	Session-6 - Create an ADLS account	60 Minutes
9	Session-7 - Ingesting Data	25 Minutes
10	Session-8 - Managing Data	60 Minutes
11	Module 3: Azure Synapse Analytics (formerly SQL Data Warehouse)
12	Session-9 - Create a Synapse workspace	60 Minutes
13	Session-10 - Ingest Data	20 Minutes
14	Session-11 - Querying Data	35 Minutes
15	Session-12 - Integrated Power BI	60 Minutes
16	Module 4: Azure Databricks for Big Data Processing
17	Session-13 - Set up Azure Databricks	60 Minutes
18	Session-14 - ETL with Databricks	60 Minutes
19	Session-15 - Machine Learning in Databricks	60 Minutes
20	Module 5: Azure Machine Learning for Advanced Analytics
21	Session-16 - Create an Azure ML workspace	60 Minutes
22	Session-17 - Training Models	60 Minutes
23	Session-18 - Deployment	60 Minutes
24	Module 6: Real-time Analytics with Azure Stream Analytics
25	Session-19 - Set up Stream Analytics Job	60 Minutes
26	Session-20 - Data Ingestion	60 Minutes
27	Session-21 - Defining Queries	60 Minutes
28	Module 7: Power BI for Visualization	60 Minutes
29	Session-22 - Connect Power BI to Azure Services	60 Minutes
30	Session-23 - Building Reports	60 Minutes
31	End to End practice at project	120 Minutes

Business Case Studies

	Topic	Duration
1	Module 1: Introduction to Business Case Studies
2	What is a Business Case Study?	40 Minutes
3	Purpose of Case Study Analysis	30 Minutes
4	Module 2: Types of Business Case Studies
5	Exploratory Case Studies	30 Minutes
6	Descriptive Case Studies	30 Minutes
7	Explanatory Case Studies	30 Minutes
8	Cumulative Case Studies	30 Minutes
9	Critical Instance Case Studies	30 Minutes
10	Module 3: Steps in Analyzing a Business Case Study	120 Minutes
11	Step 1: Read the Case Thoroughly
12	Step 2: Identify Key Issues
13	Step 3: Conduct a SWOT Analysis
14	Step 4: Analyze the Data
15	Step 5: Develop and Evaluate Alternatives
16	Step 6: Recommend Solutions
17	Step 7: Implementation Plan
18	Module 4: Frameworks for Case Study Analysis	125 Minutes
19	Porter’s Five Forces: Competitive analysis.
20	PESTLE Analysis: Macro-environmental factors (Political, Economic, Social, Technological, Legal, Environmental).
21	BCG Matrix: Product portfolio management.
22	Value Chain Analysis: Examining internal business operations for efficiency.
23	VRIO Analysis: Resources and capabilities that provide competitive advantage (Value, Rarity, Imitability, Organization).
24	Module 5: Real-World Business Case Examples	68 Minutes
25	Example 1: Apple’s Innovation Strategy
26	Example 2: Starbucks Global Expansion
27	Module 6: Tools for Case Study Analysis	30 Minutes
28	Microsoft Excel/Google Sheets
29	Miro/Lucidchart
30	Presentation Software
31	Module 7: Writing a Case Study Report	60 Minutes
32	Executive Summary
33	Background Information
34	Problem Definition
35	Data Analysis
36	Recommendations
37	Implementation Plan
38	Conclusion: Recap
39	Module 8: Tips for Effective Case Study Analysis
40	Be Objective
41	Think Like a Consultant
42	Ask Questions
43	Use Evidence

CV Preparation

	Topic	Duration
1	How to Prepare Good CV?	15 Minutes
2	Prepare Impressive CV	30 Minutes
3	Update Profile at LinkedIn, Naukri & Monster with All Required Keywords	30 Minutes

Interview Preparation (25 Interviews)

	Topic	Duration
1	How to crack Interview for Data Analyst profile?	15 Minutes
2	Interview Preparation - Session 1	60 Minutes
3	Interview Preparation - Session 2	60 Minutes
4	Interview Preparation - Session 3	60 Minutes
5	Interview Preparation - Session 4	60 Minutes
6	Interview Preparation - Session 5	60 Minutes
7	Interview Preparation - Session 6	60 Minutes
8	Interview Preparation - Session 7	60 Minutes
9	Interview Preparation - Session 8	60 Minutes
10	Interview Preparation - Session 9	60 Minutes
11	Interview Preparation - Session 10	60 Minutes
12	Interview Preparation - Session 11	60 Minutes
13	Interview Preparation - Session 12	60 Minutes
14	Interview Preparation - Session 13	60 Minutes
15	Interview Preparation - Session 14	60 Minutes
16	Interview Preparation - Session 15	60 Minutes
17	Interview Preparation - Session 16	60 Minutes
18	Interview Preparation - Session 17	60 Minutes
19	Interview Preparation - Session 18	60 Minutes
20	Interview Preparation - Session 19	60 Minutes
21	Interview Preparation - Session 20	60 Minutes
22	Interview Preparation - Session 21	60 Minutes
23	Interview Preparation - Session 22	60 Minutes
24	Interview Preparation - Session 23	60 Minutes
25	Interview Preparation - Session 24	60 Minutes
26	Interview Preparation - Session 25	60 Minutes

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