Online Data Analytics Course with AI | Live Projects – 100% Placement Assistance

Data Analytics Course with AI

Power BI

Data Visualization

Data Science

Tableau

Data Analysis

Data Analytics Course with AI

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Data Analytics Course with AI

Data Analyst Course with AI

Industry acceptable Data Analytics certification for all learner’s training which help fresher/Experienced to up-skill at corporate.

Experienced Faculty

Industry Expert Sr. Lead Analyst / Technical Analyst With 10+ Years provide workshop session @ SLA

Placement Assistance

After completion of 70% of Data Analytics training our dedicated placement team arrange interview till placement.

LAB Facility

Data Analytics Practical Training help to gain exposure like corporate level with technical test series

Data Analyst Course with AI Workshop Sessions

Real time projects & best case study makes SLA workshop very unique and lively for learners.

Admin Support

For Learner’s, Our admin team fresh batch schedule/re-scheduling classes/arrange doubt classes.

The phrase “Data Analytics” refers to the process of examining data sets to draw decisions about the information data contain. Data Analytic techniques allow you to take raw data and uncover patterns to gain an accurate and deep understanding. Error-free data analysis minimize financial loss of organization. Becoming a Data Analyst or Business Analytics as a career will be a breakthrough in 2022. Upskilling with analytics automation will be the success factor for any learner.

In order to become a Data Analytics professional, one should also have knowledge in various Data Analytics tools such as Python, Tableau, Power BI, OR, Alteryx, Generative AI, MS Excel , Automation in Excel (VBA/Macros) and MS Access, SQL. The best way to gain relevant skills and master Business Intelligence and Data Analytics tools by attending quality AI based Data Analytics Training provided by SLA Consultants Gurgaon.

Best Data Analytics Training Program with Artificial Intelligence is designed by industry experts which provides full expertise in different Data Analytics techniques like Descriptive analysis, Exploratory analysis, Diagnostic analysis, Predictive analysis, Prescriptive analysis etc. Data Analytics and Python Data Science Certification will help the learners acquire expertise in predicting customer trends and behavior, analysis, interpreting and delivering information in meaningful ways driving effective decision making along with enhancing the business productivity.

Anyone with a graduation degree is eligible to attend High-quality online AI based Data Analyst Training Course which is specifically targeted towards both fresher and working professionals who want to enter into the field of Data Analytics/Business Analytics/Data Science. The Data Analytics Course with AI is conducted by highly certified subject matter experts with the word 10 to 15 years of experience in the relevant field.

The Data Analytics Course with AI is a dedicated and intelligently designed Data Analytics Course with AI that is targeted towards an individual who is good with the numbers and figures and wants to lead a successful career in the Data Analytics field. The entire Data Analytics Course with AI is divided into five different models. The major highlight of the Data Analytics Course with AI’s content which is highly updated as per the industrial standards. It covers a wide range of advanced topics in Data Analytics with Artificial Intelligence which include Excel and VBA macros Analytics, SQL and MS Access, Python Data Visualization, Tableau and MS Power Business Intelligence(BI), R-Programming and Python. Practical Training in Data Analytics will be provided to the learner to gain experience in Business Data Analysis and acquiring technical expertise in data models, segmentation techniques, data mining techniques, database design development, etc. It will also help them to develop strong analytical skills allowing them to easily collect, organize and analyze a large amount of information with accuracy and efficiency. Upon completion of the online Data Analytics Course with AI, the participants will be able to interpret Data and Analyse results using Statistical Techniques and provide reports, develop and implement databases, Data Analytics and data collection system along with other strategies to increase the efficiency and quality, gathering information from primary and secondary data sources, identifying and analysing latest trends and patterns, filtering the information by reviewing the computer reports and performance indicators to identify any issues and much more.

The participants will also be provided with in depth understanding of Data Analysis with AI using live projects and assignments on Real world cases so that they would not require additional courses getting placement. Proper workshops and handouts will be conducted by the teachers to offer them industry relevant knowledge and resolve any of their issues. There are various other job profiles which an individual can pursue after completing the online Data Analytics Course with AI which include Data Analyst, Senior Analyst, Data Manager, Data Scientist, Business Intelligence professional, etc. Upon completion of the AI based Data Analyst training, valid certification in Data Analytics will be awarded to all the learners to help them gain the competitive edge over other candidates during the interview. 100% Job Placement Assistance will also be provided to the candidates who successfully cleared the Data Analytics Training Course by providing them resume building services along with mock interviews to make them ready for entering into the same market.

Over the last few years, Data Analytics has become one of the most important business functions worldwide due to technical Advancement which has resulted in increased generation of information on a regular basis. Every business organization regardless of their scale and size requires data in order to identify the behaviour and trends in the Business Industry which can be used to make better decision making and satisfy the needs of the customers. This has also increased the requirement for professional and knowledgeable Data Analysts in the market. There are various other reasons why one should learn Data Analytics with AI and enter into the field. Some of these reasons are mentioned below:

With the continuous generation of information which is expected to increase 50 times by 2020, there is an immense shortage of talent of skilled candidates. Professionals who are able to analyse the information will have increased requirement in the future.
According to Gartner, there will be three hundred percent increase in the jobs related to Data Analytics by the year 2025 till now it is booming. This is another reason to learn Data Analytics as it will offer the individual better job security.
Data Analytics is one field which is not restricted by one industry. Therefore, after acquiring skills and expertise in Data Analysis, you can land a job at various Business Industries such as E-commerce, Real-Estate, telecommunication, healthcare, retail and much more.
One of the best reason to learn Data Analytics is the kind of payscale received by the professional. Starting salary for Data Analytics for freshers can be 3 to 6 lakh per annum as of 2025 which can go up to 10 lakh+ per annum as per the experience.
There is also great growth opportunities in the Data Analytics field as you will be working with various other professionals. You will get to learn new things which will be beneficial for your career in the future.

Therefore, if you have made up your mind to learn Data Analytics, then you can visit our Data Analytics Training institute for registration or submit your quotation on our official website.

Data Analytics Practical with Interview Guarantee

Our Trainer:- 10+ Years of industry experience as a Data Analyst in MNC, Education:- B.Tech

Course Duration: 180 (Hours) with Highly Skilled Corporate Trainers

(Data Analytics Training) for 9 Modules – Weekdays / Weekend

SLA Consultants Gurgaon – Data Analytics Training Delivery Method:

Web / Desktop Base.
Instructor-Led Classroom Sessions.
Presentations/Demonstration/Practicals of concepts.
Handouts/Assignments/Real-time Exposure to work on Clients.

NOTE: Classes are also Available on Module Basis

Data Analyst Course with AI Programme Modules

Business Analyst Course

Module-1 Basic & Advanced Excel with Live Projects

Module 1.1: Advanced Data Handling & Cleaning

Purpose: Real-world datasets are messy. Learn to clean, transform, and prepare data efficiently.

Topics Covered

Data Cleaning Techniques
Data Protection Techniques
Removing Duplicates, Blanks, and Errors
Text-to-Columns and Flash Fill (AI Functionality in Excel)

Industry Functions

Text & String Functions: TRIM, CLEAN, SUBSTITUTE, TEXT, LEFT, RIGHT, MID, LEN
Case Formatting Functions: UPPER, LOWER, PROPER
Search & Replace Functions: FIND, SEARCH, REPLACE, VALUE, TEXTJOIN
Error & Logical Validation Functions: IFERROR, ISNUMBER, ISTEXT, ISBLANK
Date & Time Functions: DATEDIF, EDATE, EOMONTH, NOW, TODAY, DAY, MONTH, YEAR, HOUR, MINUTE, SECOND

Additional Concepts

Using Data Validation for Input Control
Dynamic Data Validation

Module 1.2: Advanced Formulas & Logical Functions

Purpose: Build dynamic, decision-based reports and formulas used across corporate functions.

Industry Functions

IF, IFS, SWITCH
AND, OR, NOT
CHOOSE, INDEX, MATCH, XLOOKUP
OFFSET, INDIRECT
Dynamic Array Functions: FILTER, SORT, UNIQUE, SEQUENCE
Nested IF and Multi-Condition Formulas

Module 1.3: Advanced Formulas & Logical Functions

Purpose: Learn to analyze, summarize, and interpret business data effectively.

Topics Covered

Understanding and Creating KPIs
Summarizing Large Datasets

Industry Functions

SUMIFS, COUNTIFS, AVERAGEIFS
SUBTOTAL, AGGREGATE
LARGE, SMALL, RANK
ROUND, ROUNDUP, ROUNDDOWN

Module 1.4: Advanced Lookup & Reference

Purpose: Master data linking across sheets and files — essential for analytics and reporting.

Topics Covered

VLOOKUP vs XLOOKUP (with practical applications)
Dynamic Range Referencing using INDEX-MATCH
Cross-Workbook Linking and Handling Broken Links

Module 1.5: Data Visualization & Dashboards

Purpose: Learn how professionals visualize and communicate insights effectively.

Topics Covered

Chart Design Best Practices
Dynamic Charts with Form Controls
Combo Charts, Sparklines, Conditional Formatting
KPI Indicators (Traffic Lights, Data Bars, Icons)
What-If Analysis for Business Scenario Testing

Module 1.6: Pivot Tables & Pivot Charts

Purpose: Master Excel’s most powerful tool for data summarization and analysis.

Topics Covered

Creating and Customizing PivotTables
Calculated Fields and Items
Grouping by Date, Month, and Quarter
Using Slicers and Timelines
Creating Hundreds of Pivot Tables in Seconds
Making Complex Pivot Tables Neat and Insightful

Module 1.7: Power Tools in Excel (for Analysts)

Purpose: Use Excel’s advanced BI tools for large-scale analytics and automation.

Topics Covered

Power Query (Merge, Append, Clean Data)
Power Pivot (Data Models, KPIs, Measures)
Connecting Excel with External Data Sources (CSV, SQL)
Introduction to RDBMS, Primary & Foreign Keys
Building Table Relationships and Data Modelling

Module 1.8: Professional Efficiency & Productivity

Purpose: Work faster, smarter, and more accurately.

Topics Covered

Advanced Shortcuts for Data Analysts
Named Ranges, Dynamic Arrays
Workbook Linking, Auditing, and Error Tracing
Formula Debugging and Error Checking
Version Control, Backup, and Template Creation

Module 1.9: Excel Integration & Productivity

Purpose: Integrate Excel with modern tools and leverage automation and AI.

Topics Covered

Excel with Google Sheets (Cloud Collaboration)
ChatGPT + Excel (AI-Assisted Formula Writing)
Excel with SQL (Data Import & Export)
Learning Techniques for Excel Shortcuts
Universal vs Non-Universal Shortcuts

Module 1.10: Advanced Dashboard Development

Purpose: Build professional, interactive dashboards.

Topics Covered

Creating Different Types of Charts
Designing Advanced Dashboards Using Summarized Data
Dynamic Dashboards with Form Controls

Assignments & Live Projects

Hands-On Practice

Module 2 - VBA Macros – Excel Automation

Introduction

Flowcharts
Step-by-Step Instructions
Process Flow Diagrams
KPIs
Algorithms

VBA/Macros Basics to Advanced

Subs, Functions, Variables, Arrays, Loops, Logic, Arrays etc

Excel Macro Language Review (VBA) Including Variables, Data Types, Constants, Arrays, Operators, Expressions, Loops, Logic Decisions and Calling
Overview Of Commanding Excel Using VBA Including
A Discussion Of Objects, Properties and Methods
The Power of Macros – What, When, How to use Macros.

Introduction to Object Oriented Concepts

Objects, Its Functions, Methods and Properties Introduction to Events
Details of Events, How & When to use of Events, Preparing to ‘Macro’ Visual Basic Editor (VBE) – Developer Tab, Security
Introduction to the VBE, Properties window, Project Explorer, Password Protection of Code How to use the VBE – Features, Options, Intelligence Technology
Debugging Mode, Bookmarks, Breakpoints, Watch Window, Immediate Window and Locals Window Inbuilt VBE Help Feature – Tips and Tricks
Form Controls vs. ActiveX Controls
Getting into the Code
Message Box and Input Box Working with Data in Excel through VBA

Data Types

Constants and Variables
Different type of data type; How and When to use Variables to Store Information.

Loops

For-Next, For-Each, Do-While, Do until, Do Loop Decision-Making and Code Branching
If-Then-Else,
Select-Case
And
Nested Conditions
What is user’s Defined Functions?
How to create & use them.

Arrays

Use of Arrays in VBA programming with one dimensional, two dimensional or multi-dimensional analysis

Excel VBA Power Programming For VBA Macros

Working with Dynamic Ranges. Protecting Worksheets, Cells and Ranges. Working with Multiple Files. Opening & Saving Files
How to Analyze Data On Multi Worksheets And Build Summary Sheets
How to Access The Windows File And Folder System To Open And Close Workbooks
How to Protect Your Code Against Errors
How to Use Excel And VBA To Create Basic Dash Boards
How to Create Your Own Custom Business Worksheet Functions In VBA
How to Create Basic Report Generation Tools Using Excel VBA, Microsoft Word And PowerPoint
How to Use The Excel Visual Basic Macro Recorder To Record Excel Tasks In VBA And Then Interpret The Code

Overview of User forms To Create Business Wizards

Working with User Forms & User Forms Events like List box, Combo box, Option Buttons, Check box, Text box, Labels, Command button, Toggle button.
How to create dynamic dashboard on user form with different controls
How to link various user form with each other to create a complete interface between user and system

Connection between Excel VBA & other platforms

How to Establish Connection Between VBA and Internet Explorer to Open any Internet Website through VBA
How to Establish Connection Between Excel VBA and power presentation to create power point through VBA
How to Establish Connection Between Excel VBA and Access database to update the data in access through VBA
How to Establish Connection Between Excel VBA and outlooks through VBA
How to Establish Connection Between Excel VBA and MS Word through VBA

Testing and Debugging Your Code

Types of Errors
Using Breakpoints
Debugging Techniques

Dialogue Boxes

UsingMsgBox Function
UsingInput Box Function
Working with FileDialog
Working GetOpenFile name Method
Working GetSaveAsFilename Method

Effective Error Handling ChatGPT AI for Excel and VBA

Module-3 - SQL and MS Access

SQL

Module 1: Introduction To Databases & SQL

What Is A Database?
Types Of Databases (Relational, Non-Relational)
What Is SQL? SQL Command Categories (DDL, DML, DCL, TCL)

Module 2: Database & Table Creation

Creating Databases // Creating Tables
Data Types In SQL
Keys & Constraints: Primary Key, Foreign Key, NOT NULL, UNIQUE, CHECK, DEFAULT

Module 3: Insert, Update & Delete

INSERT Statements
UPDATE Statements
DELETE Statements

Module 4: Basic Data Retrieval

SELECT Statements
Selecting Specific Columns
Aliases (AS)
DISTINCT Keyword

Module 5:Filtering Data

WHERE Clause
Comparison Operators
Logical Operators (AND, OR, NOT)
LIKE Pattern Matching
IN, BETWEEN, IS NULL

Module 6: Sorting & Limiting

ORDER BY
Sorting By Multiple Columns
LIMIT / TOP / FETCH

Module 7: Aggregate Functions & Grouping

GROUP BY
HAVING Clause
COUNT(), SUM(), AVG(), MIN(), MAX()
GROUP BY With Aggregates
Filtering Aggregates (HAVING)

Module 8: SQL Functions – String

CONCAT()
LENGTH() / LEN()
LOWER() / UPPER()
SUBSTRING() / SUBSTR()
TRIM(), LTRIM(), RTRIM()
REPLACE()
INSTR() / CHARINDEX()

Module 9: SQL Functions – Date/Time

NOW(), CURRENT_TIMESTAMP
CURRENT_DATE, CURRENT_TIME
DATEADD(), DATEDIFF()
EXTRACT()
DATE_FORMAT(), FORMAT()
DAY(), MONTH(), YEAR()

Module 10: SQL Functions – Math

ABS(), ROUND()
FLOOR(), CEILING()
POWER(), SQRT()
RAND()

Module 11: SQL Functions – Conversion

CAST(), CONVERT()
TO_CHAR(), TO_DATE()

Module 12: SQL Functions – Conditional

CASE Expression
NULLIF(), COALESCE()
IIF()

Module 13: SQL Functions – Window

PARTITION BY
ORDER BY (Window)
ROW_NUMBER()
RANK(), DENSE_RANK()
FIRST_VALUE(), LAST_VALUE()

Module 14: Working With Joins

Inner Join // Left Join // Right Join
Full Join // Self Join // Cross Join
Left Anti Join // Right Anti Join

Module 14: Working With Joins

Inner Join // Left Join // Right Join
Full Join // Self Join // Cross Join
Left Anti Join // Right Anti Join

Module 15: Sub queries

Subqueries In WHERE
Subqueries In SELECT
Subqueries In FROM
Correlated Subqueries

Module 16: Views

Creating Views
Updating Views
Dropping Views

Module 17: Introduction To RDBMS

What Is An RDBMS?
DBMS Vs RDBMS
Features Of RDBMS
Popular Systems: MySQL, PostgreSQL, SQL Server, Oracle

Database Concepts

Tables, Rows, Columns
Schemas & Catalogs
Primary & Foreign Keys
Candidate & Composite Keys

Data Models

Relational Model
Entities & Attributes
1-1, 1-Many, Many-Many Relationships
ER Diagrams

Module 18: SQL Server Agent (Job Scheduling)

Overview Of SQL Server Agent
Creating A Job
Adding Job Steps
Creating A Schedule

MS Access

Module 1: Introduction to MS Access

What is MS Access?
Features of MS Access
Understanding the Access interface
Databases, tables, objects overview
Differences between Access and other RDBMS

Module 2: Database Fundamentals

Creating a new database
Database file types (.accdb, .mdb)
Opening, saving, and closing databases
Navigation Pane & object organization

Module 3: Tables in MS Access

Creating tables (Design View / Datasheet View)
Field names and data types
Field properties (size, format, input mask)
Primary key selection
Creating lookup fields
Table relationships overview

Module 4: Data Types & Field Properties

Short Text, Long Text // Number, Large Number
Date/Time, Currency // Yes/No
Hyperlink // Lookup Wizard // Attachment
Field validation rules

Module 5: Working With Data

Adding records
Editing records
Deleting records
Sorting & filtering data
Searching records

Module 5: Working With Data

Adding records
Editing records
Deleting records
Sorting & filtering data
Searching records

Module 6: Keys & Relationships

Primary keys // Foreign keys
One-to-One relationships // One-to-Many relationships
Referential integrity // Relationship window

Module 7a: Queries – Types of Queries

Select Queries
Action Queries (Append, Update, Delete, Make-Table)Crosstab Queries
Find Duplicates Queries // Find Unmatched Queries

Module 7b: Queries – Concepts

Query Design View // Adding criteria
Sorting, filtering //Using expressions
Calculated fields

Module 8: Forms

Introduction to forms
Creating forms (Form Wizard, Design View)
Form layouts
Controls (Text box, Combo box, Buttons)
Binding forms to data // Navigation forms
Subforms

Module 9: Reports

Creating reports // Report Wizard // Grouping & sorting
Headers & footers // Summary reports
Printing & exporting reports

Module 10: Importing & Exporting Data

Import from Excel // Export to Excel
Importing text files // Linking tables (external data)
Connecting to SQL databases

8 Major Points to Learn MS Access in Analytics

1. Easy Data Management for Non-Technical Users
2. Relational Database Capabilities
3. Powerful Querying (SQL Support)
4. Perfect for Small & Medium Projects
5. Integration With Excel & Business Tools
6. Forms & Reports for Business Insights
7. Automation Through Macros & VBA
8. Best for Teaching Structured Data Concepts

Module 4 - MicroSoft Power BI ▷ BI & Data Visualization

Microsoft Power BI – Introduction

What is MSPBI& Scope
Learn the common work flow in Power BI
Building blocks of Power BIand its relations
Quick demo how to create a business dashboard in MSPBI
MSPBI components

MS Power BI – Getting Business Data

Get data in shape for use with Power BI
Combining two or more data sets (source data) for reporting
Tackling messy data in MS Power BI
Clean &Transform data

MS Power BI -Data Visualization

Create and customize visualization
Use combination charts
Create and format slicers
Map visualizations
Visualizations utilization
Use tables and matrixes
Long live bubbles
scatter charts in action
Advanced funnel and waterfall charts
Drive fast dashboard insights with gauges and numbers
Color your visualization world with colors
shapes and scales
Adding personal touch
logo etc. to reports and dashboards
Display and present your dashboard in a way you want with summarize data
Control how your report elements overlap with each other
Learn to drill into hierarchies
Manage how levels are shared (Z-order in reports)
How to use R visuals in MSPBI

MS Power BI -Data Exploring & Sharing

Quick insights in Power BI Service
Create and configure a dashboard
Share dashboard with your organization
Display and edit visuals- tiles
full screen
Get more space on your dashboard
Install and configure a personal gateway
Excel and MSPBI
Import and excel table into Power BI
Import excel files with data models and power view sheets
Connect One Drive for business to MSPBI
Excel data in Power BI summary

MS Power BI – DAX (Data Analysis Expression) Application

Setting up Data Models with DAX

DAX for creating tables and columns
Rows vs. query vs. filter context
DAX for calculated tables and columns
Creating a date table
Calculated column for costs
Data cleaning with DAX
Connecting data from different tables
Methods to create DAX measures
Advantages of explicit measures V2
DAX and measures
Using variables
Basic statistical measures
Quick measures

Power BI – Common DAX Measures

Filtering and counting with DAX
Understanding different filter functions
Using different filters with DAX
Filter ALL the data
Calculating with a filter
Analyzing across dimensional tables
Iterating functions
DIY iterating functions
Iterating functions in Power BI
Practice with iterating functions
More iterating functions
Use of RANKX()

Power BI – Redefine DAX

Logical functions
Interpreting SWITCH()
Logical functions in Power BI
IF() for formatting tables
Exploring SWITCH()
Grouping
Row-level security
Applying row-level security
Managed roles in Power BI
Creating an email list
Implementing RLS

Power BI – Advanced DAX

Table manipulation functions
Summary of SUMMARIZE()
Table manipulations using DAX
SUMMARIZE() the facts
ADDCOLUMNS()? No problem!
Time intelligence functions
Time intelligence functions output
Time intelligence in Power BI
Use of TOTALYTD()
Use of SAMEPERIODLASTYEAR()

Module 9: Reports

Creating reports // Report Wizard // Grouping & sorting
Headers & footers // Summary reports
Printing & exporting reports

Module 10: Importing & Exporting Data

Creating reports // Report Wizard // Grouping & sorting
Headers & footers // Summary reports
Printing & exporting reports

Module 5 - Tableau

Tableau – Introduction

Getting Started with Tableau
Overview Of Tableau
Tableau Architecture

Tableau – Connecting to Data

Managing Metadata
Managing Extracts
Data Sources
Cross-Database Joins
Data Aggregation And Data Ports
Tableau Charts
Bar Charts and Stacked Bars Data Blending
Tree Maps and Scatter Plots
Individual Axes
Blended Axes
Dual Axes
Combinational Chart

Tableau -Data Visualization/Visual Analytics

Drill Down
Hierarchies
Sorting
Filtering
Grouping
Trend
Reference Lines
Forecasting
Clustering
Analysis with Cubes
MDX

Tableau -Developing First Bar Chart

Connecting Tableau to Data File
Navigating Tableau
Calculated Fields
Adding
Colors
Labels
Formatting

Tableau – Time Series, Maps and Aggregation

Data Extracts and Time Series
Understanding Granularity, Aggregation and Level of Details
Default Location in Maps
Custom Geo Coding
Symbol Map and Filled Map

Tableau- First Dashboard

Into Section
Joining Data In Tableau
Working With Maps
Hierarchies
Scatter Plot
Applying Filters in Different Sheets
Creating 1st Dashboard
Creating 2nd Dashboard

Tableau -Blending Data and Dual Axis Charts

Duplicate Values
Multiple Fields
Data Blending
Dual Axis Chart
Building Calculated Fields

Tableau -Table Calculation

Downloading Dataset and Connection
Mapping
Building Table Calculation For Gender
Bins and Distributions for Age
Tree Map Chart

Tableau – Advanced Dashboard

Advanced Dashboard

Tableau – Storytelling

Storyline and Storytelling

Tableau – Data Preparation

Data Format
Data Interpreter
Multiple Columns And Pivot
Metadata Grid

Advanced Data Preparation

Module 6.1 - Python Data Science with Live Projects

Module 6.1.1: Introduction to Python Programming

Purpose:Build a strong foundation in Python syntax and programming concepts essential for data analysis.

Topics Covered

Introduction to Python What is Python and why it’s popular for Data Analysis Installing Python, Jupyter Notebook, and Anaconda
Python Basics Data Types: int, float, str, bool Variables and Constants Input and Output operations Type Conversion and Casting
Operators Arithmetic, Logical, Comparison, and Assignment Operators
Control Flow Conditional Statements: if, elif, else Loops: for and while Loop Control Statements: break, continue, pass

Module 6.1.2: Data Structures in Python

Purpose:Learn how to store, organize, and manipulate data efficiently using Python’s built-in structures.

Topics Covered

Core Data Structures Lists, Tuples, Sets, Dictionaries
Operations Indexing and Slicing Adding, Updating, and Removing Elements
Comprehensions List Comprehension Dictionary Comprehension
Common Built-in Functions len(), max(), min(), sum(), sorted(), type()

Module 6.1.3: Functions, Modules, and Packages

Purpose:Learn how to write reusable and modular Python code for analytical workflows.

Topics Covered

Functions
- Defining and Calling Functions
- Return Statements and Parameters
- Default, Positional, and Keyword Arguments
Modules
- Using Built-in Modules (math, datetime, os, random)
- Creating and Importing Custom Modules
Packages Installing and Managing Packages using pip

Module 6.1.4: Working with Files

Purpose:Learn how to import, read, write, and manage external datasets effectively.

Topics Covered

File Handling Basics — open(), read(), write(), close()
Reading and Writing Files (CSV, TXT)
Working with File Paths using os and pathlib
Writing Processed Data to Files

Module 6.1.5: Introduction to Data Analysis with Pandas

Purpose:Master the most widely used Python library for real-world data manipulation and analysis.

Topics Covered

Pandas Basics Introduction to Series and Data Frame
Reading & Writing Data read_csv(), to_csv(), read_excel(), to_excel()
Exploring Data head(), .tail(), .info(), .describe()
Selecting & Filtering Data .loc[], .iloc[] for row/column selection Conditional filtering (df[df[‘column’] > value])

Data Cleaning

Handling Missing Data (fillna, dropna)
Adding, Renaming, and Dropping Columns
Sorting and Grouping Data (sort_values, groupby)

Module 6.1.6: Data Visualization with Matplotlib & Seaborn

Purpose:Develop the ability to present data visually for better insights and reporting.

Topics Covered

Introduction to Matplotlib – Basic Plot Types: Line, Bar, Pie, Histogram, Scatter Customizing Visuals (titles, labels, colors, legends)
Seaborn for Statistical Visualization – Plot Types: barplot, countplot, boxplot, heatmap, pairplot
Styling and Aesthetics
Exporting Charts Saving visuals in .png and .pdf formats

Module 6.1.7: Data Cleaning & Preprocessing

Purpose:Learn how to prepare raw datasets for analysis — an essential industry skill.

Topics Covered

Handling Missing Values
Detecting & Removing Duplicates
Changing Data Types (astype())
String Operations on Columns (.str.upper(), .str.strip(), .str.replace())
Date Conversion using pd.to_datetime()
Identifying and Removing Outliers
Basic Feature Engineering for better model performance

Module 6.1.8: Introduction to NumPy

Purpose:Learn efficient numerical computing — the backbone of Python data analytics.

Topics Covered

NumPy Basics
Arrays vs Lists
Creating and Manipulating Arrays
Array Operations
Indexing, Slicing, and Broadcasting Vectorized Computations
Mathematical Functions mean(), median(), std(), sum(), sqrt(), dot()
Random Module Generating Random Numbers (np.random.rand(), np.random.randint())

Module 6.1.9: Mini Projects & Practical Assignments

Purpose:Apply your learning to hands-on, real-world projects.

Mini Projects

Sales Data Analysis (Pandas + Matplotlib) Cleaning and visualizing monthly sales data
COVID Data Dashboard Using Pandas and Seaborn to visualize cases and recovery trends
Customer Segmentation (CSV File Analysis) Filtering, grouping, and reporting based on demographic data

Module 6.2 - Machine Learning

Module 6.2.1: Introduction to Machine Learning

Purpose:Understand the foundations, workflow, and use cases of Machine Learning in the real world.

Topics Covered

What is Machine Learning?
Difference between AI, ML, and Deep Learning

Types of Machine Learning:

Supervised
Unsupervised
Reinforcement Learning (overview)

Real-world Applications of ML (Finance, Healthcare, Retail, etc.)

Machine Learning Workflow:

Problem Definition → Data Collection → Preprocessing → Modeling → Evaluation → Deployment

Module 6.2.2: Python for Machine Learning

Purpose:Build programming readiness for ML with essential Python tools.

Topics Covered

Quick Revision of Python Data Analysis
Key Libraries for ML:

NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn

Data Importing and Exploration
Descriptive Statistics & Correlation Analysis
Feature Selection and Importance Overview

Module 6.2.3: Data Preprocessing & Feature Engineering

Purpose:Prepare raw data for training accurate and reliable models.

Topics Covered

Handling Missing Values (SimpleImputer, fillna)
Removing Duplicates and Outliers
Encoding Categorical Data:
- One-Hot Encoding
- Label Encoding
Feature Scaling:
- Standardization (Z-score)
- Normalization (MinMaxScaler)
Splitting Data (Train-Test Split)

Module 6.2.4: Supervised Learning — Regression Algorithms

Purpose:Build models that predict continuous outcomes.

Topics Covered

Simple Linear Regression Understanding line of best fit Evaluation metrics: MAE, MSE, RMSE, R²
Multiple Linear Regression Handling multiple predictors

Module 6.2.5: Supervised Learning — Classification Algorithms

Purpose:Train models to classify or categorize data points.

Topics Covered

Logistic Regression Sigmoid function and decision boundary
K-Nearest Neighbors (KNN) Distance metrics and K-value selection
Decision Trees Gini impurity and information gain
Random Forest Classifier Ensemble learning and feature importance
Support Vector Machines (SVM) Hyperplanes and kernel tricks
Naïve Bayes Classifier Probability-based classification

Module 6.2.6: Unsupervised Learning Algorithms

Purpose:Discover hidden patterns and relationships in unlabeled data.

Topics Covered

Clustering
- K-Means Clustering
- Hierarchical Clustering (Dendrograms)
- DBSCAN (Density-Based Clustering)
Dimensionality Reduction PCA (Principal Component Analysis) t-SNE (for visualization)
Association Rule Learning Apriori Algorithm Market Basket Analysis

Module 6.2.7: Model Evaluation, Optimization & Validation

Purpose:Improve model accuracy and generalization.

Topics Covered

Train-Test Split and Cross Validation (K-Fold CV)
Bias-Variance Tradeoff
Grid Search & Random Search for Hyperparameter Tuning
Ensemble Learning Concepts: Bagging and Boosting

Module 6.2.8: Advanced Topics in Machine Learning

Purpose:Get exposure to advanced tools and concepts used in modern ML.

Topics Covered

Introduction to Pipelines in Scikit-learn
Feature Selection Techniques (Recursive Feature Elimination)
Time Series Forecasting (Intro)
Handling Large Datasets
Saving and Loading Models (pickle, joblib)

Module 6.2.9: Model Deployment (Basics)

Purpose:Learn how ML models are integrated into real-world systems.

Topics Covered

Exporting Models with joblib and pickle
Deploying Models Locally or on Web
Introduction to APIs and Integrations

Module 6.2.10: Real-World Machine Learning Projects

Purpose:Apply all concepts to realistic datasets and business problems.

Projects

Predictive Analytics (Regression) Predict House Prices based on area, location, and features.
Classification Project Credit Card Fraud Detection or Employee Attrition Prediction.
Unsupervised Learning Customer Segmentation using K-Means and PCA.

2+ End-to-End ML Projects

Machine Learning Interview Questions

Module 7-Alteryx Data Analytics

Alteryx- Introduction

What exactly is Alteryx?
Why are We learning Alteryx
What is Meant by Alteryx Designer
Alteryx Designer User Interface
User and Workflow Configuration

Alteryx–Alteryx Designer

Tool Palettes
Configuration
Favorite Palettes
Workflow Canvas

Alteryx- Parsing Data

Format Data
Find Replace Delimiters

Alteryx–Data Containing

Using Conditional Statements in Formulas
Format Data/ Time Fields
Use values From Previous/SubseQuent Rows in Formulas

Alteryx–Data Restructuring/Data Processing

Split data, skip records, use a record as field headings, pivot and unpivot data and trim and split fields
Input Data
Dynamic Rename
Text to columns
Transpose
Cross Tab
Formula
Directory
Comment
Sample
Tool Container
Select
Filter
Output Data
Record Id
Unique

Alteryx– Join Data from Various Source

Filter
Summarize
Browse
Union
Join Multiple
Input Data
Formula
Join
Output Data
Data Filter
Generate Row

Alteryx–Data Handling

Impute Values
Data Cleansing
Formula
Append Field
Random Sample
Unique
Running tool

Alteryx–Create Static Reporting

Table
Charts
Layout
Date time Now
Email
Sort
Render
Resort map
Report Text

Alteryx–Images

Create Points
Spatial Match
Find Nearest
Trade area
Distance
Special info

Alteryx–Pharse Data with Regex

List Box
Numeric Up Down
Checkbox
Control Parameter
Action / Image
File Browse / Radio Button

Module 8-R-Programming Business Analytics

Module 9 - Generative Artificial Intelligence

Download Business Analyst Course Brochure

Data Analytics Course with AI

Business Analyst Course with AI

Data Analyst with AWS

Data Science

FAQ

What tools and programming languages are covered in the Data Analytics with AI course?

How is Artificial Intelligence (AI) integrated into the curriculum?

Are there hands-on projects?

Where are the classes held?

Can I take this course online?

What is the duration of the training program?

Does SLA Consultants offer job placement assistance?

Testimonials

Rahul Pal

From my point of view, I’ll strongly recommend SLA Consultants, the best Training Institute for Analyst courses. I am pursuing my Data Analyst Course from this institute under the guidance & knowledge of Data Analyst trainers, my two modules (advance Excel and VBA) of the course has been completed. I must say, they have good training faculty, as well as have the great infrastructure for learning and practicing.

Rahul Pal

Rohit Bhagat

I strongly recommend SLA, the best Training Institute for doing courses. I am doing my Data Analyst course in the Head Office, till now my two modules(Advanced Excel and VBA) have been completed. Its been good experience with a trainer, as they shared me a lot of knowledge in brief. At the institute, trainers and admin staff is very cooperative.

Rohit Bhagat

Deepak Sharma

I have completed Advanced Excel & Visual Basic Automation training course from SLA Consultants. I had amazing experience after completion of the training program and I would like to say thanks to the trainer, who elaborate solution for all the problems very quickly at the same time with very easy Technic to better understanding. Trainers are very kind and helpful. I would like to rank him 5 out of 5. I am so much obliged and feeling grateful, thanks a ton for the great support by trainers and thank you SLA Consultants.

Deepak Sharma

MIS & Data Analyst Executive

Amit Kumar

I hope, my review may help to those who are searching for an institution where they can enhance their skills and get a placement as well. I have joined SLA Consultants for complete MIS course, my trainer is one of the best teacher of my life. Who are searching for a institute joined it immediately without hassle & wasting your time. Trainer will teach you both theoretical as well as practical knowledge, also prepare you for interviews. The best thing about trainer is that they help you even after you completion of your course, share queries on e-mail or Whats-App your query and you will get your problem resolved. My over all experience was awesome.

Amit Kumar

MIS & Data Analyst Executive

Vinay Tiwari

My experience in SLA is quite well.I have taken classes for both modules Advance Excel and VBA Macros. Whenever I raised for any doubt and to be honest my all queries and doubt were sorted out patiently. I must say my trainer was quite supportive and patiently explained everything. Even though I have taken classes on weekend basis, but never feel like that the course is running or missing anywhere. And now I am too confident about Excel and VBA after completion of training under expert trainers. I will always recommend everyone to Join SLA Consultants if they are interested in MIS and RPA etc..

Vinay Tiwari

MIS & Data Analyst

Abhishek Bharti

I have great experience in SLA Consultants for Excel and VBA Macros with expert trainers.

Abhishek Bharti

MIS Executive

Hemant Harshwal

I have joined SLA Consultants for Advanced Excel and VBA. Have gone through no. of classes and got good knowledge about Excel and VBA. Our trainerwas very supportive and patiently explains every thing. He is very cooperative apart of training he also suggest regarding our career.

Hemant Harshwal

Data Analyst

Himanshu Nautiyal

I have done MIS & VBA course form SLA Consultants under the guidance of Anoop Sir, he has a very good knowledge & experience. He is a professional Trainer & his way of teaching is very good. It is great experience for me to grow with my skill & work efficiency. It is very good Platform who wants to build-up their career in MIS. Also thanks to Swati Mam for Co-ordinate with us and help me to find a good platform.

Himanshu Nautiyal

Fortune Marketing Pvt.Ltd.

Rajesh Pratap Singh

I’ve joined SLA Consultants for Advance excel and VBA It helps me to move my career. Especially Anoop Sir is very good teacher and his teaching style is awesome. One thing I want to tell you about new joiners who has no experience in Industry, they can build-up their career platform through SLA Consultants.

Rajesh Pratap Singh

Rahul Kumar

I have done MIS & VBA Training form SLA Consultants under the guidance of MR. ANOOP YADAV, he has a very good knowledge & experience in Corporate & MNC. He is professional Trainer & his way of teaching is as per the corporate requirement. I’d great experience for me to grow my skill & work efficiency. It is very good pelt from who wants to build-up their career in MIS.

Rahul Kumar

MIS Executive at ASIAN COLOUR COATED ISPAT LTD

Neeraj Gupta

SLA Consultants is too good & very helpful. If u want to achieve something in your life so please join today SLA Consultants. Especially I would like to thank Swati Mam, Anoop Sir.

Neeraj Gupta

MIS Executive at Shriram Automall India Ltd

Archit Khandelwal

Thanks to SLA consultants for giving me such type of opportunity, Great Institute with great teaching faculty. SLA is one of the class-apart institutions for those who learn something. I got a job in Fortune marketing Pvt Ltd as MIS Executive. SLA give me the confidence of ” I CAN “

Archit Khandelwal

MIS Executive at Fortune Marketing Pvt. Ltd

Anil Kumar

It was one of the best decisions to join SLA consultants for my course. The course that I pursued here was very well planned and executed. I’m highly satisfied with Anoop Sir. The lectures were easy to understand & industrial based & every doubt of mine was properly explained. I would recommend SLA consultants to all those who are willing to grow in their careers and do well.

Anil Kumar

MIS Coordinator at IQOR

Kumar Gautam

I joined MIS/VBA training at SLA. This type of practical oriented classroom training is very helpful & who’ll follow Anoop sir classes with this approach ensures that they will learn completely about subject in short period of time. “SLA Consultants” is the best for learning job-oriented classroom programs. Thanks to Anoop sir and Swati for the best placement support.

Kumar Gautam

MIS Coordinator at IQOR

Ummed Ali

SLA Consultants is better institute to learn practical training courses than any others. it provides the best training to their students. The teaching staff is very knowledgeable especially Anoop Sir for MIS and VBA courses. I learned a lot there and better career path.

Ummed Ali

MIS Executive at Evaxo pharma Pvt. Ltd

Bhavani Singh

The experience with SLA was phenomenal. It trained me to become industry ready and exposed me to various important work practices. The staff is extremely cordial and cooperative. The faculty members are the experienced and experts in the subjects taught by them. I thank SLA for the quality services and placement assistance provided by them.

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MIS Executive at G.D. FOODS MFG. (I) PVT LTD.

Anil Kumar Pal

Thanks to SLA consultants, my company values me a lot. I can churn out data from a huge database within a few minutes and keep the management happy. The ever cooperative trainers of SLA have made me capable of doing that and I will be grateful to them.

Anil Kumar Pal

MIS Executive at Recharge it Now

Priyanka Tiwari

I did not know what to do in life. Then I saw the ad of SLA Consultants. After getting knowledge of all their course offerings, I selected MIS and loved it from the start. Thank you for making my career and helping me get a good life SLA.

Priyanka Tiwari

MIS Executive at Concepts & Solutions

Santosh Kumar

When I joined, I didn’t have a clue about MIS Management and now my friends call me an expert of MIS. All thanks to SLA Consultants who filled me with great knowledge and software training without charging a lot of money.

Santosh Kumar

MIS Executive at Jai Shree Stationers Pvt. Ltd.

Kapil Negi

Data Management has always attracted me. SLA Consultants turned this hobby in a professional skill by teaching me all about MIS Management. I got a good job now and I am very happy with my life.

Kapil Negi

MIS Executive at Genpect

Aditya Pratap

I’ve completed the MIS training from SLA Consultants and now I believe that SLA provides the excellent & quality training. I got placed in a reputed company with complete placement support provided the SLA placement team.

Aditya Pratap

MIS Executive at CS Datamation Research Services Pvt Ltd

Avinash

The team of trainers working with SLA is amazing. The support staff is always there to help and Arbind Sir was a great guide. I will never forget my time at SLA and I thank them for the job they helped me get after I completed my course.

Avinash

MIS Executive at Serco Global Services

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My love for Data Management was turned into a career opportunity by SLA Consultants. They helped me learn all latest MIS software and made me a champion of Data Management. I have a great career path thanks to the SLA Team.

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MIS Executive at Renovision Automation

Sushil kumar yadav

Thanks to SLA consultants, my company values me a lot. I can churn out data from a huge database within a few minutes and keep the management happy. The ever cooperative trainers of SLA have made me capable of doing that and I will be grateful to them.

Sushil kumar yadav

MIS Executive at Bharti Infratel

Rajbir Sharma

SLA Consultants played the role of a friend, philosopher and guide in my career. They helped me learn complex software and complicated terminologies in such a manner that I now excel at MIS Management. I also love the job they have helped me get.

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Sr. MIS Executive at Computer Junction Pvt. Ltd.

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I think SLA Consultants is the best place for skill development. They made me a professional from a fresher and I have seen them do the same for hundreds of students. I highly recommend them to very student or professional seeking career growth.

Pawan Gupta

MIS Executive - Rosmerta Technology Ltd.

Anand Kumar Jha

MIS Executive - Rosmerta Technology Ltd.

Nazia Praveen

From the first day I entered the office of SLA Consultants, they helped me. I completed the admission process swiftly and started learning MIS whenever it was convenient. Now I am working in a full time job that’s not hectic but enjoyable.

Nazia Praveen

MIS Executive - Globalite Retails Pvt Ltd

Hariom Agarwal

The staff, trainers, and management of SLA Consultants is great. These people really help freshers like me to get a good job. They have changed thousands of lives and I am happy to say that mine was also changed by them. So thank you.

Hariom Agarwal

MIS Executive - Globalite Retails Pvt Ltd

Indresh Kumar

I didn’t know anything about MIS management when I joined SLA Consultants. They helped me to learn the craft of managing, sorting and presenting data and now I am a valuable asset in my company. Thank You, SLA Consultants. I will always be grateful to you.

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MIS Executive - Recharge it Now

Md Sadik

SLA Consultants played the role of a friend, philosopher and guide in my career. They helped me learn complex software and complicated terminologies in such a manner that I now excel at MIS Management. I also love the job they have helped me get.

Md Sadik

MIS Executive at Evaxo Pharma Pvt. Ltd.