Data Analytics
June 5, 2025 2025-06-07 2:16Data Analytics
Become a Data Analytics – Secure Your Dream Job
Master Full Stack Java Development with hands-on training, expert mentorship, and placement support. start your journey toward a successful IT career today!
Start Learning For Free
Lectures & Assignments curated by Top Tech Professionals
Unlimited Placement Calls from Day 1
From the very first day, we ensure our candidates receive unlimited placement calls, giving them maximum opportunities to connect, interview, and secure their dream roles with our hiring partners.
We build your technical foundation, enhance your practical skills, and prepare you for real-world interviews through:
💡 Live Project Experience
💼 Mock Interviews with Experts
🧠 Aptitude & Soft Skills Training
📈 Career Counseling and Resume Building
Watch yourself transform your future
Anjali Kanki
Rehman Khan
Monu Kumar
Anjali Gochade
Sherya Lad
Vashnavi Wakar
Our Hiring Patners
You can list your partners or instructors's brands here to show off your site's reputation and students can trust you more.
Comprehensive Data Analytics Syllabus.
Designed for Industry Readiness with Practical, Hands-on Implementation
Data Analytics Course in Pune – By Advanto Infotech
Join the leading Data Analytics Course in Pune and learn how to tackle real-world business challenges using data-driven insights. This 100% Job-Assured Data Analytics Course is perfect for recent graduates and professionals aiming to launch a successful career in data analytics. Gain practical knowledge of data analytics applications in enterprises and prepare yourself to become a skilled data analytics professional in a fast-growing industry.
At Advanto Infotech, we offer an integrated learning experience with ongoing career support to help you shape your future innovatively. Our unique training approach lets you work on projects from day one, alongside expert-led sessions. Each batch receives continuous guidance from experienced mentors throughout the course.
Work on real datasets and industry-relevant projects to build a strong portfolio.
Stay competitive by mastering the most in-demand tools and skills such as Python, R, Power BI, Tableau, and more.
We understand every learner is unique. Our course offers personalized learning paths and one-on-one support to help you achieve your goals, whether you’re new or experienced in data analytics.
Our commitment to your success continues beyond the course with career
Our training is delivered by highly experienced and qualified professionals who have in-depth industry expertise. They are committed to providing relevant, hands-on knowledge to help students excel in their careers.
Why Choose Data Analytics
Learn from industry experts and seasoned data analytics professionals who bring real-world experience and mentorship.
Our comprehensive curriculum covers all essential areas—from data collection and preprocessing to advanced analytics and data visualization techniques.
Build a versatile skill set that prepares you for diverse roles in data analytics.
We emphasize practical, hands-on learning with projects and exercises that enable you to apply concepts immediately.
Course Fees and Duration
Advanto provides an affordable Data Analytics course with flexible payment plans, offering the best value among institutes in Pune.
The course duration is typically 100 hours (weekends), ideal for students and working professionals.
Visit our office to get detailed information on fees, course duration, and other specifics about the Data Analytics course in Pune.
100% Placement Assistance
Advanto infotech is one of Pune’s most trusted Java Full Stack Developer training institutes with a proven track record. We provide 100% placement assistance, including:
Unlimited placement calls
Personalized interview preparation
Resume building and mock sessions
With over 8 years of training experience, we’ve successfully placed hundreds of students in top MNCs and IT companies. Completing this course gives you a near-guaranteed pathway to employment in the tech industry.
- Introduction to Programming
- Variables & Arithmetic Expressions
- Functions
- Data Types
- Conditions and Conditional statements
- Lists
- OOPS
- Intro to Excel
- Importing data
- Formatting in Excel
- Excel Formulae
- Data Validation
- Calculations
- Lookup and Reference
- Pivot Tables
- Charts
- What-if Analysis
- Intro to Macros
- Introduction to SQL
- DDL Statements
- DML Statements
- DQL Statements
- Aggregate Functions
- Date functions
- Union, Union All & Intersect Operators
- Joins
- Views & Indexes
- Sub-Queries
- Exercise on SQL
- Python Introduction
- Variables
- Functions
- Python Operators
- Python Flow Controls
- Conditional Statements
- Loops
- Strings
- List
- Tuple
- Dictionary
- List Comprehension
- User-defined Functions
- Function Arguments
- Lambda Functions
- Introduction to NumPy
- NumPy Array
- Creating NumPy Array
- Array Attributes
- Array Methods
- Array Indexing
- Slicing Arrays
- Array Operation
- Iteration through Arrays
For Loop- While Loop
- Do While Loop
- Break Statements
- Pandas Data frame – Introduction
- Data frame Creation
- Reading Data from Various Files
- Understanding Data
- Accessing Data frame Elements using Indexing Data frame Sorting
- Ranking in Data frame
- Data frame Concatenation
- Data frame Joins
- Data frame Merge
- Reshaping Dataframe
- Pivot Tables
- Cross Tables
- Dataframe Operations
- Checking Duplicates
- Dropping Rows and Columns
- Replacing Values
- Grouping Dataframe
- Missing Value Analysis & Treatment
- Visualisation using Matplotlib
- Plot Styles & Settings
- Line Plot
- Multiline Plot
- Matplotlib Subplots
- Histogram
- Boxplot
- Pie Chart
- Scatter Plot
- Message
- Message Passing
- Message Sender
- Message Receiver
- Visualisation using Seaborn
- Strip Plot
- Distribution Plot
- Joint Plot
- Violin Plot
- Swarm Plot
- Pair Plot
- Count Plot
- Heatmap
- Summary Statistics
- Missing Value Treatment
- Dataframe Analysis using Groupby
- Advanced Data Explorations
- Introduction to Machine Learning
- Machine Learning Modelling Flow
- Parametric and Non-parametric Algorithms
- Types of Machine Learning
- Introduction of Linear Regression
- Types of Linear Regression
- OLS Model
- Math behind Linear Regression Decomposition Variability
- Metrics to Evaluate Model
- Feature Scaling
- Feature Selection
- Regularisation Techniques
- Project – Property Price Prediction
- Class Assessment on Linear Regression
- Intro to Logistic Regression
- Maximum Likelihood Estimation
- Performance Metrics
- Performance Measures
- Bias-Variance Tradeoff
- Overfitting and Underfitting Problems
- Cross Validation
- Project – Vaccine Usage Prediction
- Home Assignment on Logistic Regression
- Introduction to Decision Tree
- Entropy
- Information Gain
- Greedy Algorithm
- Decision Tree: Regression
- Gini Index
- Tuning of Decision Tree-Pruning
- Project – Heart Disease Prediction
- Introduction to Random Forests
- Averaging
- Bagging
- Random Forest – Why & How?
- Feature Importance
- Advantages & Disadvantages
- Project on random forest – Taxi Fare Prediction
- Class Assessment on Classification
- Inner Class
- Nested Class
- Different types of Nested Classes
- What is Clustering?
- Prerequisites
- Cluster Analysis
- K-means
- Implementation of K-means
- Pros and Cons of K-means
- Application of K-means
- Project on K-means Clustering – E-commerce Customer Segmentation
- Introduction to Hierarchical Clustering
- Types of Hierarchical Clustering
- Dendrogram
- Pros and Cons of Hierarchical Clustering
- Project on Hierarchical Clustering – Travel Review Segmentation
- Home Assignment on Clustering
- Prerequisites
- Introduction to PCA
- Principal Component
- Implementation of PCA
- Case study
- Applications of PCA
- Project on PCA – Real Estate Data Analysis using PCA
- Understand Time Series Data
- Visualising Time Series Components
- Exponential Smoothing
- Holt’s Model
- Holt-Winter’s Model
- ARIMA
- Project – Forecasting the Sales of a Furniture Store
- Introduction to Statistics
- Random Variables
- Descriptive Statistics
- Measure of Central Tendency
- Measure of Dispersion
- Skewness and Kurtosis
- Covariance and Correlation
- What is Probability?
- Events and Types of Events
- Sets in Probability
- Probability Basics using Python
- Conditional Probability
- Expectation and Variance
- Probability Distributions
- Discrete Distributions
- – Uniform
- – Bernoulli
- – Binomial
- – Poisson
- Continuous Distributions
- – Uniform
- – Normal
- Probability Distributions using Python
- Introduction to Hypothesis Testing
- Terminologies used in Hypothesis Testing
- Procedure for testing a Hypothesis
- Test for Population Mean
- Small Sample Tests
- Large Sample Tests
- One-way ANOVA
- Assumptions
- ANOVA Hypothesis
- Post Hoc Test
- Chi-Square Test
- Chi-Square Test Steps
- Chi-Square Example
Data visualisation with Tableau and Power BI
- Introduction to Tableau
- Data Connection
- Tableau Interface and Basic Chart Types
- Working with Metadata
- Visual Analytics
- Mapping
- Calculations
- Dashboard and Stories
- Introduction
- Interface
- Data Connections
- Data Transformation
- Advance Data Transformation
- Project – Stock Data analysis
- Exam – Tableau and Power BI Exam
- Ensemble Techniques
- What is Ensembling?
- Bootstrap Method
- Bagging
- Boosting
- XGBoost
- AdaBoost
- Introduction to KNN
- Working of KNN
- Applications of KNN
- Advantages and disadvantages of KNN
Some detailed project based on Regression
Some detailed project based on SQL, Tableau
Some detailed project based on Excel, Power BI
- Introduction to Linux
- Linux Commands
- Resume-building
- GitHub Project Portfolio
- Interview Preparation
- Mock Interviews
- Career Mentorship
