Data Analyst Training in Mumbai with Placement

COURSE OVERVIEW

Mumbai’s premier Data Science Training Institute equips you with advanced skills in data analytics, AI/ML, and programming—tailored for finance, media, and e-commerce sectors.

Core Data Science Concepts: From data ingestion and cleaning to exploratory analysis and feature engineering.
Statistical Mastery for Analytics: Dive deep into probability, distributions, p-values, and A/B testing used in Mumbai’s financial hubs.
Data Manipulation & Stunning Visuals: Leverage Python tools (Pandas, NumPy, Seaborn, Matplotlib) to transform and present data.
Machine Learning in Action: Implement classification, regression, clustering, and NLP models with Mumbai business use cases.
Deploy High-Performance Models: Learn model validation, regularization, and ensemble techniques to avoid overfitting.
Scale with Big Data Technologies: Hands-on training in Spark, Hadoop, and AWS/GCP for large-scale data processing.
Influence with Data Storytelling: Create executive dashboards and presentations to drive decisions in Mumbai’s fast-paced industries.

✅ Real-time case studies | ✅ Practical hands-on labs | ✅ Certification Guidance

✅ Beginner Friendly ✅ Industry Projects ✅ Job Ready Skills

WHO SHOULD JOIN?

Anyone who are willing to transform their careers for trending Jobs of 21st Century

CAREER OUTCOMES

Laptop/Desktop with at least 8 GB of RAM, good capacity Hard Drives and good internet connectivity.
No programming knowledge needed, foundational knowledge will be provided

COURSE CURRICULUM

25+ Course Topics • Hands-on Labs • Real-Time Practice

MODULE 1: FOUNDATIONS

01 Introduction to Data Analytics Topics

What is Data Analytics vs Data Science vs Business Intelligence
Roles and responsibilities: Business Analyst, Data Analyst, BI Developer
Analytics workflow: Data collection → Analysis → Visualization → Insights → Action
Real-world case studies from industry (finance, retail, e-commerce, healthcare)
Career paths and salary benchmarks in analytics

02 Python Environment Setup for Analytics Topics

Installing Python, Jupyter Notebook, VS Code
Package managers: pip, conda
Setting up virtual environments
Introduction to IDE best practices

03 Python Fundamentals for Analytics Topics

Language fundamentals: variables, data types, operators
Control flow: if-else, loops (for, while)
String manipulation and formatting
Lists, tuples, dictionaries for data handling
Functions: defining, parameters, return values

MODULE 2: DATA MANIPULATION & EXPLORATION

04 NumPy Essentials Topics

NumPy arrays vs Python lists: performance benefits
Array creation, indexing, slicing
Mathematical operations on arrays
Broadcasting concepts
Statistical functions (mean, median, std, percentile)
Practical: Working with multi-dimensional datasets

05 Pandas for Data Analysis (Core Module) Topics

Series and DataFrame fundamentals
Creating DataFrames from CSV, Excel, SQL databases
Indexing and selecting data
Viewing and inspecting data (head, tail, info, describe)

06 Data Cleaning and Transformation Topics

Handling missing values (dropna, fillna, interpolation)
Removing duplicates
Data type conversions
Handling outliers

07 Data Manipulation Topics

Filtering and sorting
Groupby operations and aggregations
Pivot tables and crosstabs
Merging, joining, concatenating DataFrame

08 Time Series Basics Topics

DateTime handling
Resampling and rolling windows
Trend analysis

09 Exploratory Data Analysis (EDA) Theory Topics

Understanding data distribution
Identifying patterns and relationships
Statistical thinking for analysts
Types of analysis: univariate, bivariate, multivariate
Hypothesis formation from data exploration

MODULE 3: DATA VISUALIZATION & STORYTELLING

10 Matplotlib Fundamentals Topics

Figure and axis objects
Line plots, bar charts, histograms, scatter plots
Customization: colors, markers, line styles
Legend, labels, titles, annotations
Grid and axis formatting
Multiple plots: subplots and figure layouts

11 Advanced Visualization with Seaborn Topics

Statistical visualization concepts
Categorical plots: bar, box, violin, strip plots
Distribution plots: histograms, KDE plots
Relationship plots: scatter, regression plots, heatmaps
Color palettes and styling
FacetGrid for multi-dimensional analysis

12 Interactive Dashboards with Plotly & Streamlit Topics

Plotly basics: interactive charts and hover information
Creating dashboards with Streamlit
Deploying Streamlit apps to cloud (Streamlit Cloud, Heroku)
Real-time data updates
Dashboard best practices

13 Data Storytelling Topics

Principles of data visualization
Choosing the right chart for the message
Narrative structure: context, conflict, resolution
Presenting insights to non-technical stakeholders
Creating compelling business report

MODULE 4: STATISTICS FOR BUSINESS DECISIONS

14 Descriptive Statistics Topics

Central tendency: mean, median, mode
Spread: range, variance, standard deviation, IQR
Skewness and kurtosis
Outlier detection and handling (IQR method, Z-score)
Weighted statistics

15 Probability Basics Topics

Fundamentals: sample space, events, probability rules
Conditional probability and Bayes' theorem
Independence and dependence
Real-world application scenarios

16 Inferential Statistics Topics

Sampling concepts and distributions
Confidence intervals: for mean and proportion
Hypothesis testing: null vs alternative hypotheses
T-tests, Z-tests, chi-square tests
P-values and significance levels
Type I and Type II errors

17 Correlation and Simple Regression Topics

Correlation: Pearson, Spearman, Kendall
Scatter plots and relationship identification
Simple linear regression: model interpretation
R² and RMSE for model evaluation
Residual analysis

18 A/B Testing for Business Topics

Experiment design and setup
Sample size calculation
Statistical significance testing
Business impact vs statistical significance
Case studies: marketing, product optimization

MODULE 5: SQL FOR DATA ANALYSTS

19 SQL Fundamentals Topics

SELECT, WHERE, ORDER BY, LIMIT
Filtering with AND, OR, NOT, IN, BETWEEN
DISTINCT and COUNT

20 Data Aggregation & Joins Topics

GROUP BY and aggregation functions (SUM, AVG, MAX, MIN, COUNT)
HAVING clause
INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN
Self-joins and multiple joins

21 Intermediate SQL Topics

Subqueries and CTEs (Common Table Expressions)
Window functions: ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD
Date functions and time-based analysis
CASE statements for conditional logic

22 Practical Analytics Queries Topics

Customer segmentation queries
Cohort analysis
Funnel analysis
Revenue analysis and trends
Practice: Real-world dataset analysis

MODULE 6: CAPSTONE PROJECT

23 End-to-End Analytics Project Topics

Objective: Analyze a real-world dataset and present business insights
Phases:
1. Data sourcing and initial exploration
2. Data cleaning and preparation
3. EDA with statistical analysis
4. Hypothesis testing and validation
5. Creating visualization dashboard
6. Business recommendations and ROI impact
Deliverables:
Cleaned dataset with documentation
Jupyter notebook with analysis
Interactive dashboard (Streamlit or Plotly)
Executive summary report
Presentation to stakeholders
Example Projects:
Customer retention analysis (e-commerce)
Sales trends and forecasting (retail)
User behavior analysis (SaaS platform)
Healthcare outcome analysis

24 TOOLS & TECHNOLOGIES USED Topics

Languages: Python 3.9+
Data Manipulation: Pandas, NumPy
Visualization: Matplotlib, Seaborn, Plotly, Streamlit
Databases: SQL (MySQL, PostgreSQL)
Notebooks: Jupyter, Google Colab
Deployment: Streamlit Cloud, GitHub

25 POWER BI TOOLS and PROJECTS Topics

POWER BI TOOLS and PROJECTS

HANDS-ON LABS YOU WILL WORK ON

WHAT'S INCLUDED IN THIS PROGRAM

40 Live Sessions

90+ hrs Recordings

70% Hands-On Training

30% Essential Theory

100+ hrs Lab Practices

Guided Implementation

24×7 Lab Access

Practice Anytime

Resume Building

LinkedIn Optimization

Job Support

Post-Placement Support

Real-World Projects

Industry Capstone Projects

Internship Opportunities

Hands-on Exposure

Technical Mentorship

Expert-Led Guidance

Career Guidance

Personalized Roadmap

GitHub Portfolio

Project Documentation

Interview Preparation

Mock Interviews

Course Completion Certificate

Verified Achievement
Course Completion
Certification Support
Project Portfolio Included

VIEW CERTIFICATE

LEARNING MODES

Choose the mode that fits your schedule and learning style.

CLASSROOM
TRAINING

Instructor-led training
Interactive sessions
Real-time doubt clearing
Hands-on practice

CHOOSE CLASSROOM

LIVE ONLINE
TRAINING

Live interactive classes
Learn from anywhere
Recorded sessions
Flexible schedule

CHOOSE LIVE ONLINE

SELF-PACED
LEARNING

Learn anytime, anywhere
HD recorded video lessons
3 years course access
Practice at your own speed

CHOOSE SELF-PACED

FAQs

Each of our live sessions are recorded. In case if you miss any, you can request us to share the link of that particular session.

Once you get registered, our back-end team will share you the details to join the session live over online portal which can be accessed through a browser.

For practical execution, our trainer/technical team will provide server access details to the student.

Yes. We do provide the step-by-step document which you can follow and if required our technical team will assist you.

Live-Online training is where you can have live session with the trainer and clarify queries parallely.

Pre-recorded sessions are the recorded videos that will be provided to you that you can see, listen and learn anytime at ur feasible place. For doubts in the videos you can mail the trainer regarding the same.

You can contact our support team, or just drop an email to online@akswave-trainings.com with your queries.

The course material and recorded videos which are provided during the course period. You can download it anytime.

Visit our website regularly to check discount offers time to time. However, we provide discount for single participant & special discount for 2 or more participants.

* If request for cancellation is made within 2 days of enrolment for class, 100% refunded.

* If request made after 2 days, then Refund is made after deduction of administration fee.

Enquire Now

Download Brochure

Data Analyst Training in Mumbai

COURSE OVERVIEW

WHO SHOULD JOIN?

CAREER OUTCOMES

PRACTICE LIKE A REAL PROFESSIONAL

What You Will Learn to Do in Real-World Projects

COURSE CURRICULUM

HANDS-ON LABS YOU WILL WORK ON

WHAT'S INCLUDED IN THIS PROGRAM

40 Live Sessions

70% Hands-On Training

100+ hrs Lab Practices

24×7 Lab Access

Resume Building

Job Support

Real-World Projects

Internship Opportunities

Technical Mentorship

Career Guidance

GitHub Portfolio

Interview Preparation

Course Completion Certificate

MEET YOUR TRAINER

STUDENT SUCCESS STORIES

PLACEMENT ASSISTANCE

Resume
Preparation

Mock
Interviews

Technical
Interview Q&A

Company
Referrals

Placement
Support

UPCOMING BATCHES

LEARNING MODES

CLASSROOM
TRAINING

LIVE ONLINE
TRAINING

SELF-PACED
LEARNING

FAQs

READY TO BECOME AN ORACLE DBA EXPERT?

Enquire Now

Download Brochure

Data Analyst Training in Mumbai

COURSE OVERVIEW

WHO SHOULD JOIN?

CAREER OUTCOMES

PRACTICE LIKE A REAL PROFESSIONAL

What You Will Learn to Do in Real-World Projects

COURSE CURRICULUM

HANDS-ON LABS YOU WILL WORK ON

WHAT'S INCLUDED IN THIS PROGRAM

40 Live Sessions

70% Hands-On Training

100+ hrs Lab Practices

24×7 Lab Access

Resume Building

Job Support

Real-World Projects

Internship Opportunities

Technical Mentorship

Career Guidance

GitHub Portfolio

Interview Preparation

Course Completion Certificate

MEET YOUR TRAINER

STUDENT SUCCESS STORIES

PLACEMENT ASSISTANCE

ResumePreparation

MockInterviews

TechnicalInterview Q&A

CompanyReferrals

PlacementSupport

UPCOMING BATCHES

LEARNING MODES

CLASSROOMTRAINING

LIVE ONLINETRAINING

SELF-PACEDLEARNING

FAQs

READY TO BECOME AN ORACLE DBA EXPERT?

Resume
Preparation

Mock
Interviews

Technical
Interview Q&A

Company
Referrals

Placement
Support

CLASSROOM
TRAINING

LIVE ONLINE
TRAINING

SELF-PACED
LEARNING