Full Stack Analytics
- Time Duration: 2-3 Months
- Skill Level : Advance Course
- Certificate : Yes
COURSE DESCRIPTION:
Want to become a data-driven decision maker? The best Full Stack Analytics course at Unividya takes you through the entire analytics journey—from raw data to real business insights. This hands-on program teaches you how to collect, clean, analyze, and visualize data using top tools like Python, R, SQL, Tableau, and Power BI. Whether you’re preparing for roles in data analytics, BI, or business strategy, this course equips you with full-stack skills that today’s employers demand.
LEARNING OUTCOMES:
Understand the complete analytics lifecycle: data collection, processing, analysis & reporting
Build ETL pipelines using SQL, Python, and tools like Apache Spark
Analyze large datasets and create visual dashboards with Tableau and Power BI
Perform exploratory data analysis (EDA) and build predictive models for business insights
Who Can Join?
The Full Stack Analytics course at Unividya is perfect for students, fresh graduates, working professionals, or career switchers who are eager to dive into data.
No advanced tech background? No problem. If you’re comfortable with basic math and want to turn data into insights, this course will guide you step by step—from the basics to advanced analytics tools.
What You’ll Learn!
In the Full Stack Analytics course at Unividya, you’ll:
Learn data collection, cleaning, and processing techniques
Use SQL, Python, and R for data analysis and ETL workflows
Build interactive dashboards using Tableau and Power BI
Perform exploratory data analysis (EDA) and predictive modeling
Work on real projects that mirror business analytics challenges
- Time Duration: 2-3 Months
- Skill Level : Advance Course
- Certificate : Yes
COURSE DESCRIPTION
The Full Stack Analytics course is a comprehensive program designed to equip students with the skills and knowledge required to excel in the dynamic fields of data and business analytics. This course covers the entire data analytics lifecycle, including data collection, cleaning, processing, and visualization, as well as advanced statistical analysis, machine learning, and predictive modeling. Students will learn to use popular tools and technologies such as Python, R, SQL, Tableau, and Power BI to analyze complex datasets and derive actionable business insights.
LEARNING OUTCOMES
- Understand the end-to-end analytics lifecycle, from data collection and processing to visualization and reporting.
- Gain proficiency in tools and technologies for data extraction, transformation, and loading (ETL) processes, such as SQL, Python, or Apache Spark.
- Develop skills in building and managing data pipelines for seamless data integration across multiple sources.
- Learn to create data models and perform exploratory data analysis (EDA) to derive meaningful insights.
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast