Certified Career Courses

Data Analytics Course in Pune

100% Job Oriented

Experts Trainers

Live Projects

Interview Preparation

Enroll Now

Finest Data Analytics Classes in Pune | Data Analytics Course in Pune with Placement

Are you stuck trying to master data analytics? Tired of courses that don’t teach the skills companies actually want? Technoscripts has launched an Expert Driven Data Analytics Course in Pune to make you a professional analyst, whether you’re starting as a fresher or trying to upskill yourself. A Candidate can learn tools & technologies like Python, SQL, Tableau, and Power BI, plus hot topics like machine learning and data visualization, so join our Data Analytics Classes in Pune and become Industry Ready.

This course can be pursued by students, engineers, or professionals with a Graduation degree in B.Tech, M.Tech, BCA, MCA, or BE. You’ll dive into practical projects, learning how to clean data, build dashboards, and predict trends. In 2024 and 2025, Technoscripts placed over 2,742 students in top companies worldwide. We’ve hosted 33+ placement drives and 12+ walk-in interviews, creating 8,900+ job opportunities.

Our mentors are industry pros with at least 2 years of teaching and 24+ years of combined experience in data analytics. They’ll guide you every step of the way, from hands-on training to nailing job interviews. With our Data Analytics Training in Pune with Placement, you get personalized coaching, resume help, and mock interviews to land your dream role. Sign up with Technoscripts now and kickstart your data analytics career!

Features and Data Analytics Course in Pune with Placement

Technoscripts is Accredited by NASSCOM and also ISO certified making it one of the most trusted Training institutes around the city. There are a handful of features we provide along with the Data Analytics Classes in Pune with Placement making us very successful and positively impacting a candidate's journey much easier as compared to before. Technoscripts provide Live Project Mentorship from industry experts, providing students with hands-on training experience making them industry ready.

Mock interviews are conducted for Technical, HR and managerial rounds by industry experts, leading candidates to learn from their mistakes and calm their nerves down during actual interviews. Along with this Linkedin Optimization Workshops from experts and ATS resume creation sessions of industrial and HR managers, making their digital profiles outshine the competition. This Data Analytics Course in Pune with Placement is available in online, offline and hybrid modes of training providing flexibility and ease of learning to all the college students and working professionals.

Technoscripts also provide up to date study material along with the access to a dedicated Learning management System. We also provide internship letters and experience letters, enhancing the value of the profile of a candidate. Our mentors have a cumulative experience of more than 20+ years in training and mentoring students along with 15+ Years of cumulative experience in the field of Data Analytics. This enhances the learning experience of our Candidates and they also get an opportunity to learn from the best, knowing how the most difficult of the challenges can be overcome with the slightest of troubles. Our Team of mentors also guide in and out throughout the course mini projects and Live Projects making us the finest Training institute for Data Analytics Classes in Pune with Placement.

NASSCOM Accredited

ISO Certified

Live Projects

Mock Interviews

Online/Offline Training

Internship Letter

Course Material and LMS

Profile Building

Industry Experts

Data Analytics Course in Pune with Placement Syllabus

Curriculum

Module 1: Intro Data Analytics

What is data analytics? Role in business and industry

Descriptive, diagnostic, predictive & prescriptive

Collection, cleaning, analysis & reporting

Career paths: Data analyst, business analyst, BI developer

Hands-on: Set up Python, Jupyter Notebook, and Excel

Module 2: Python Coding & Basics

Variables & data types (int, str & list)

Control structures: if-else, loops (for, while)

Functions: Defining, arguments, return statements

Exception handling: try, except

Hands-on: Write simple Python scripts (e.g., basic calculator)

Module 3: Advanced Python for Analytics

Data structures: Lists, dictionaries, sets

List comprehensions and lambda functions

File handling: Reading/writing CSV, JSON

Libraries: Introduction to NumPy, Pandas

Hands-on: Process a dataset with Python

Module 4: Mathematics for Data Analytics

Algebra: Equations, functions, matrices

Statistics: Mean, median, standard deviation

Probability: Basics, conditional probability

Percentages and ratios for business metrics

Hands-on: Calculate stats with Python

Module 5: Statistics for Data Analytics

Measures of spread & skewness

Hypothesis testing & confidence intervals

Correlation: Pearson, Spearman

Sampling methods: Random, stratified

Hands-on: Perform statistical tests in Python

Module 6: Excel for Data Analytics

Excel basics: Cells, formulas, functions (SUM, VLOOKUP)

Pivot tables and charts for summarization

Data cleaning: Text to columns, remove duplicates

Conditional formatting and data validation

Hands-on: Analyze a dataset in Excel

Module 7: Advanced Excel Techniques

Advanced functions: INDEX, MATCH, IFERROR

Macros and VBA: Automating repetitive tasks

Power Query: Data import and transformation

Power Pivot: Building data models

Hands-on: Create a dashboard with Power Pivot

Module 8: Data Collection & Sources

Structured, unstructured & semi-structured

Databases, APIs & web scraping

Data quality: Accuracy, completeness

Tools: Open datasets, Kaggle, Google Sheets

Hands-on: Collect data from an API

Module 9: Data Cleaning and Preprocessing

Handling missing values: Imputation, deletion

Removing duplicates and outliers

Data transformation: Normalization, encoding

Tools: Pandas, OpenRefine

Hands-on: Clean a messy dataset

Module 10: Data Wrangling, Pandas

Pandas: DataFrames, Series, indexing

Merging and joining datasets

Grouping and aggregating data

Pivoting and reshaping data

Hands-on: Wrangle a complex dataset

Module 11: SQL Basics & Analytics

SQL: Tables, queries, SELECT, WHERE

Joins: Inner, left, right, full

Aggregation: COUNT, SUM, AVG

Subqueries for complex analysis

Hands-on: Write SQL queries on a sample database

Module 12: Advanced SQL Techniques

Window functions: RANK, ROW_NUMBER

Common Table Expressions (CTEs)

Optimizing queries for performance

Connecting SQL with Python (e.g., sqlite3)

Hands-on: Analyze data with advanced SQL

Module 13: Data Visualization with Python

Libraries: Matplotlib, Seaborn, Plotly

Plot types: Bar, line, scatter, heatmap

Customizing visuals: Titles, labels, colors

Interactive plots with Plotly

Hands-on: Create visualizations for a dataset

Module 14: Data Visualization with Tableau

Tableau basics: Connecting to data, worksheets

Building charts: Bar, pie, line, maps

Calculated fields and parameters

Dashboards: Combining multiple visuals

Hands-on: Build a Tableau dashboard

Module 15: Power BI for Analytics

Power BI: Data import, DAX basics

Visuals: Bar, column, slicers

Data modeling: Relationships, hierarchies

Publishing and sharing reports

Hands-on: Create a Power BI report

Module 16: EDA

EDA & Uncovering patterns

Techniques: Summary stats, distributions

Visual tools: Box plots, histograms

Correlation analysis and feature selection

Hands-on: Perform EDA on a dataset

Module 17: Introduction to Machine Learning for Analytics

ML basics: Supervised vs. unsupervised learning

Role of ML in predictive analytics

Scikit-learn: Python’s ML library

Key terms: Features, labels

Hands-on: Explore an ML dataset

Module 18: Linear Regression for Analytics

Predicting continuous outcomes (e.g., sales)

Model fitting: Least squares method

Evaluation: R-squared, Mean Absolute Error

Assumptions: Linearity, normality

Hands-on: Build a linear regression model

Module 19: Logistic Regression for Analytics

Predicting binary outcomes (e.g., churn)

Sigmoid function and probabilities

Evaluation: Accuracy, confusion matrix

Feature importance in classification

Hands-on: Implement logistic regression

Module 20: Clustering for Analytics

Unsupervised learning: Grouping data

K-Means clustering: Algorithm, k selection

Applications: Market segmentation

Evaluation: Silhouette score

Hands-on: Cluster customer data

Module 21: Time Series Analysis

Time series: Trends, seasonality, cycles

Moving averages and smoothing

Models: ARIMA basics

Forecasting business metrics

Hands-on: Forecast sales data

Module 22: Into A/B Testing

A/B testing & Hypothesis setup

Designing experiments: Control vs. treatment

Statistical significance: p-values, t-tests

Applications: Marketing, product testing

Hands-on: Analyze an A/B test result

Module 23: Customer Analytics

Customer segmentation: RFM analysis

Churn prediction and retention strategies

Lifetime value (CLV) calculation

Behavioral analysis with data

Hands-on: Segment customers in Python

Module 24: Financial Analytics

Key metrics: ROI, profit margins, revenue

Budget forecasting and variance analysis

Risk analysis: Volatility, credit risk

Tools: Excel, Python for finance

Hands-on: Analyze financial data

Module 25: Marketing Analytics

Campaign performance: CTR, conversion rates

Attribution models: First-touch, last-touch

Funnel analysis: Drop-off points

Tools: Google Analytics, Python

Hands-on: Analyze a marketing campaign

Module 26: Web Analytics

Web metrics: Page views, bounce rate, sessions

Tools: Google Analytics, Adobe Analytics

Tracking user behavior: Events, goals

Module 27: Big Data Basics

What is big data? Characteristics

Tools: Hadoop, Spark overview

PySpark for large-scale data processing

Handling massive datasets

Hands-on: Process data with PySpark

Module 28: Data Engineering for Analytics

Extract, Transform & Load

Data pipelines: Airflow basics

Cloud storage: AWS S3, Google Cloud

Data lakes vs. data warehouses

Hands-on: Build an ETL pipeline

Module 29: Cloud Tools for Analytics

Cloud platforms: AWS, Azure, GCP

AWS QuickSight for visualization

Google BigQuery for large-scale queries

Azure Data Factory for pipelines

Hands-on: Use a cloud tool for analysis

Module 30: Data Storytelling

Communicating insights to stakeholders

Structuring reports: Problem, analysis, solution

Visual design: Clarity, impact

Presenting data-driven recommendations

Hands-on: Create a report with visuals

Module 31: Ethics in Data Analytics

Bias in data: Sources, mitigation

Privacy: Data anonymization, GDPR

Ethical use of analytics: Transparency

Case studies: Ethical dilemmas

Hands-on: Analyze a dataset for bias

Module 32: Version Control for Analytics

Git basics: Commit, branch, merge

GitHub: Repositories, collaboration

Versioning datasets and scripts

Team workflows for analytics

Hands-on: Push a project to GitHub

Module 33: R Programming for Analytics

R basics: Vectors, data frames, functions

Data manipulation: dplyr, tidyr

Visualization: ggplot2 for plots

Statistical modeling in R

Hands-on: Analyze data with R

Module 34: Advanced Visualization Techniques

Storytelling with advanced visuals

Tools: D3.js for custom visuals

Geospatial analysis: Maps, heatmaps

Animated and interactive dashboards

Hands-on: Build an advanced visualization

Module 35: Industry Applications - Part 1

Healthcare: Patient analytics, cost analysis

Finance: Fraud detection, portfolio analysis

Retail: Inventory optimization

Case studies: Real-world examples

Hands-on: Solve a healthcare problem

Module 36: Industry Applications - Part 2

Marketing: Campaign ROI analysis

Manufacturing: Supply chain analytics

E-commerce: Sales forecasting

Case studies: Industry successes

Hands-on: Solve an e-commerce problem

Module 37: Placement Preparation - Technical Skills

Resume building: Highlight analytics projects

Portfolio: Showcase dashboards, models

Technical interviews: Python, SQL, Excel

Mock technical interviews

Hands-on: Solve analytics challenges

Module 38: Placement Preparation - Professional Skills

Behavioral interviews: Communication, teamwork

Job search: LinkedIn, Pune tech networks

Role expectations: Data analyst, BI analyst

Mock HR interviews

Hands-on: Prepare a job pitch

Module 39: Capstone Project - Part 1

Project selection: Real-world analytics problem

Planning: Data source, tools, deliverables

Initial work: Data collection, cleaning

Mentor feedback session

Hands-on: Submit project proposal

Module 40: Capstone Project - Part 2

Implementation: Analysis, visualization, insights

Presentation: Dashboard or report

Delivery: Demo to peers and recruiters

Placement support: Showcase to employers

Final submission: Project report and demo

Online and Offline Training for Data Analytics Course in Pune with Placement

Online Training for Data Analytics Classes in Pune with Placement	Offline Classes for Data Analytics Training in Pune with Placement
Technoscripts Provide online training in Data Analyst Course in Pune with Placement inclusive of all the features: Mock Interviews, Linkedin Optimization, provision of internship letter, NASSCOM Accreditation and ISO certification, Up-to date course material and access to dedicated Learning Management System. The mentors and fees both remain the same for the online mode of this training program. Technoscripts also provide facility to students in online mode to come and attend classes in offline mode too making it a hybrid model with 100% Placement Assistance. These batches are also available in both weekend and weekday modes.	Technoscripts provides training in offline mode from expert industry mentors also providing training and mentorship to the students in online mode also. Hands on Live projects and practical implementation in our advanced smart classes provides excellent experience to the candidates. Regular doubt sessions are also conducted on a weekly basis or every 15 days making it easy for candidates to clear their doubts on priority basis. Recording of lectures is also provided to students in case of failure to attend live classroom training sessions on our Learning management System. These batches are also available in both weekend and weekday modes.

Online Training for Data Analytics Classes in Pune with Placement

Offline Classes for Data Analytics Training in Pune with Placement

Technoscripts Provide online training in Data Analyst Course in Pune with Placement inclusive of all the features: Mock Interviews, Linkedin Optimization, provision of internship letter, NASSCOM Accreditation and ISO certification, Up-to date course material and access to dedicated Learning Management System. The mentors and fees both remain the same for the online mode of this training program. Technoscripts also provide facility to students in online mode to come and attend classes in offline mode too making it a hybrid model with 100% Placement Assistance. These batches are also available in both weekend and weekday modes.

Technoscripts provides training in offline mode from expert industry mentors also providing training and mentorship to the students in online mode also. Hands on Live projects and practical implementation in our advanced smart classes provides excellent experience to the candidates. Regular doubt sessions are also conducted on a weekly basis or every 15 days making it easy for candidates to clear their doubts on priority basis. Recording of lectures is also provided to students in case of failure to attend live classroom training sessions on our Learning management System. These batches are also available in both weekend and weekday modes.

Batch Schedule for Data Analytics Course in Pune with Placement

Batch Schedule for Data Analytics Classes in Pune with Placement	Timmings
Morning Batch Online (Weekday)	9 to 11 AM
Afternoon Offline Batch (Weekday)	12 to 2 PM
Afternoon Hybrid Batch (Weekday)	2 to 4 PM
Evening Hybrid Batch (Weekend)	5 to 7 PM

Benefits of pursuing Data Analytics Course in Pune with Placement

All the Candidates pursuing this training program gain hands-on knowledge for industrial and corporate implementation, Logic building and problem solving skills in the field of Data Analytics.

This Course also helps candidates with building their digital profiles and exploring more about the latest trends and skill requirements in the top MNC companies and also startups around the globe.

Data Analytics Classes in Pune with Placement also provides all the candidates with Networking Opportunities and builds a strong network, which can be utilised later to overcome challenges and flourish new opportunities.

Students gain confidence in their respective domain and after completion of this course, it also opens up other opportunities in different fields like Advance Artificial Intelligence, Data Science, Data Analytics, Full Stack Python Development, Machine Learning and much more.

Which is the best institute for Data Analytics Course in Pune with Placement?

Technoscripts Stands the best training institute for Data Analytics Classes in Pune with Placement because in 2025 alone we have placed more than 384+ Students and conducted more than 17+ Placement drives along with 9+ walk-in interview drives.

Students who pursued this Course have noticed a 18% increase of them getting placed because of our features like conducting mock interviews, linkedin optimization and ATS friendly resume building.

Professionals notice 13.2% additional hikes and 11.5% additional ease in switching companies with better position and salary after pursuing this course at Technoscripts making us one of the top most Training institutes in Pune.

Technoscripts is now trusted by 10000+ students in the field of IT training across 10 major domains like Advanced Embedded Systems, Artificial Intelligence, Automotive and EV Technologies, Data Science, Data Analytics, Power BI and Tableau, Full Stack Development and Machine learning.

Feedback from Students on Data Analytics Course in Pune with Placement