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Offered by: VVR Technologies Duration: 8 Weeks (2 Months) Mode: Online / In-Person / Hybrid Level: Beginner to IntermediateIn today’s data-driven world, every decision — from marketing to operations — relies on analytics. This 2-month Data Science & Data Analytics Fast Track Program by VVR Technologies helps you build the most essential and market-ready skills to start your journey in the world of data.
You’ll learn how to clean, analyze, visualize, and interpret data, using modern tools like Python, Power BI, SQL, and Excel — without needing prior coding experience. By the end of the program, you’ll have hands-on experience with real projects, ready to showcase your portfolio to employers.
Core Tools: Python (Pandas, Matplotlib), SQL, Power BI, Excel Optional: Tableau, Jupyter Notebook
Build strong foundations and get comfortable with tools What is Data Science, Analytics, and Business Intelligence Real-world examples (Finance, Healthcare, Retail, HR) Understanding data: structured, semi-structured, unstructured Overview of the Data Lifecycle Tools setup: Excel, Python (Anaconda/Jupyter), Power BI Explore your first dataset in Excel Create simple charts & pivot tables Install Python and practice simple scripts Learn Python only for data tasks (no deep programming). Python basics (variables, data types, lists, loops, functions) Introduction to NumPy and Pandas Reading and writing data files (CSV, Excel) Cleaning and summarizing data Load a dataset in Pandas and clean missing values Find top-selling products or top customers using Python Learn to fix messy data — the most important real-world skill. Identifying missing, duplicate, or incorrect data Data transformation (filter, merge, sort, rename columns) Handling categorical data (label encoding) Formatting data for analysis. Clean HR or sales data Create a clean, ready-to-analyze dataset Learn to create charts, dashboards, and insights. Visualizing data with Matplotlib & Seaborn Creating interactive dashboards in Power BI Choosing the right chart for your data Storytelling with data: how to explain insights clearly Create a Power BI dashboard (e.g., Sales Performance, HR Turnover) Present 3 key insights from your analysis Learn the language that every analyst uses to query data. Introduction to Databases & SQL SELECT, WHERE, ORDER BY, GROUP BY Aggregations & joins Using SQL with real datasets (SQLite / MySQL) Find monthly sales trends using SQL queries Combine SQL and Python to fetch and analyze data Learn business-focused analytics and visualization. Advanced Excel formulas (VLOOKUP, IF, INDEX-MATCH) Charts, slicers, and dashboards in Excel Data connections in Power BI Creating KPIs and reports Build a sales dashboard in Excel Publish a Power BI report Understand how data leads to predictions and decisions. Mean, median, mode, standard deviation Correlation and trend analysis Introduction to predictive analytics Linear Regression (with hands-on demo) Real-world use: Forecasting sales or churn prediction Predict next month’s sales using simple regression Compare data patterns using correlation Apply everything you learned end-to-end. Customer retention analysis Sales performance dashboard Employee attrition analysis Website traffic & conversion analytics Clean dataset Visual dashboard (Power BI or Excel) Insight summary / presentation deck
Resume and portfolio building for Data Analyst roles Real interview questions from 2025 market Intro to AI tools for analysts (ChatGPT, Copilot, Gemini) Basics of Cloud Data (AWS, Azure, Google BigQuery)By the end of this course, learners will be able to:
Clean, analyze, and visualize real-world data Build dashboards and present insights Write SQL queries for analysis Perform basic predictive analytics Build a small data portfolio for job applicationsMaster the art of front-end, back-end, databases, APIs, and deployment in one comprehensive program. Learn how to design, build, and scale web applications end-to-end.
Master the tools and frameworks that power modern AI — from prompt engineering to building generative applications.
Develop end-to-end data science expertise — from data wrangling to AI-powered predictions — using real-world business datasets.
Learn how to drive growth, brand visibility, and online engagement through data-driven digital marketing strategies.
Strengthen your expertise in protecting digital systems and networks. Learn modern cyber security tools, threat-analysis techniques.