Top-Notch Faculty
Trainers at Pune Software Technologies are passionate about training, and carry 12+ years of industry experience.
Trainers at Pune Software Technologies are passionate about training, and carry 12+ years of industry experience.
Our industry-relevant course curriculum is tailored to provide practical exposure with the theory.
Learners will work on real time business scenarios to get application knowledge.
Enroll in our placement-focused workshops, where you’ll receive expert guidance on professional CV building, interview preparation and job search strategies. You will receive continuous career support, job updates, and mentoring until you get your dream job.
Analyze retail sales data to identify trends across products, regions, and time. Use Python libraries to clean, explore, and visualize data through charts and dashboards. Deliver insights on top-selling products and monthly sales performance.
Predict customer churn using historical telecom or subscription data. Clean and preprocess the dataset, then apply logistic regression and decision trees. Evaluate model performance using metrics like accuracy.
Explore Airbnb listing data to uncover patterns in pricing and popularity. Use visualizations like box plots, heatmaps, and interactive dashboards.
Draw insights based on room type, location, and review count.
Perform time series analysis on stock price data to forecast future trends. Use decomposition, ARIMA, and smoothing techniques to build models. Visualize trends, seasonality, and predictions using Python tools.
Segment customers into groups using K-means clustering based on buying behavior. Normalize data, reduce dimensions using PCA, and visualize clusters. Provide marketing insights based on identified customer segments.
Predict diseases like diabetes using patient health datasets. Perform hypothesis testing, build machine learning models, and evaluate results. Deliver a concise report with medical insights and predictive accuracy.
A data analyst is responsible for analyzing data, creating visual reports, identifying trends, and helping business teams make informed decisions using tools like Python, Pandas, Excel, and visualization libraries.
Focuses on bridging the gap between business and data teams. Uses data analysis to support business strategies, generate reports, and recommend improvements. Strong communication and data storytelling skills are key here.
Analyzes market data, consumer behavior, and trends to help businesses understand market dynamics. Skills in data visualization and storytelling are crucial here.
Manages and analyzes data related to operations, logistics, or customer support. Often involves cleaning datasets, generating insights, and improving operational efficiency.
Entry-level role in data science. Involves basic machine learning, statistical analysis, and building predictive models—especially useful after completing modules like regression, classification, and clustering in your course.
I’m really thankful for the training I received in the Data Analyst co...
The Data Analyst course was well-structured and beginner-friendly. I l...
I had a great experience with the Data Analyst course. The concepts we...
