Data Analytics

Program Overview

60 Days – Foundation in Data Analytics with Python

Gain essential skills in data analysis, covering Python basics, data manipulation with Pandas, and numerical computations with NumPy. Learn data visualization using Matplotlib and Seaborn, and conduct exploratory data analysis (EDA) on real-world datasets.

• Key Topics: DataFrames, statistical operations, univariate/bivariate analysis, hands-on EDA case studies.

90 Days – Intermediate Data Analytics with Python

Build on foundational skills to master advanced data cleaning, transformation, and visualization. Explore predictive analytics with regression models and complete end-to-end projects focused on sales forecasting and customer behavior analysis.

• Key Topics: Advanced Seaborn and Plotly visualizations, machine learning for analytics, interactive dashboards, real-world projects.

180 Days – Master Data Analytics with Python

Master advanced techniques, including big data analytics with PySpark, statistical modeling, and advanced machine learning algorithms. Automate data pipelines, deploy analytics dashboards, and integrate solutions with cloud platforms. Conclude with capstone projects to showcase your expertise.

• Key Topics: Hadoop and Spark, Bayesian statistics, clustering, Flask/Django integration, multi-domain projects.

Program Benefits

• Comprehensive Learning: Covers everything from foundational Python to advanced machine learning and big data.
• Practical Focus: Real-world projects and case studies for actionable insights.
• Career-Oriented: Guidance on building a portfolio, automating workflows, and deploying analytics solutions.
• Flexible Durations: Tailored modules for foundational, intermediate, and advanced learners.

This program ensures a deep understanding of data analytics, equipping you to solve real-world challenges and excel in the data-driven industry.