Data Analytics Training

Description:

Ededge Learning, a pioneering Ed-Tech organization dedicated to fostering youth potential and bridging the gap between education and industry experience, is offering a Data Analytics Training & Internship Program. This remote internship provides aspiring data analysts with the opportunity to work on real-world data projects, gaining crucial skills and practical exposure in data analytics, business intelligence, and machine learning.

Through this internship, selected individuals will work closely with Ededge’s esteemed data science team, engaging in activities such as data collection, preprocessing, visualization, and model development. Interns will explore practical applications of Exploratory Data Analysis (EDA) using Python, as well as utilize tools like Tableau and no-code platforms to extract meaningful insights from business datasets. Emphasis will be placed on risk analytics in sectors like banking and finance, while also exploring applications in commerce, procurement, and shared systems such as bike-sharing models.

The internship also includes hypothesis testing (e.g., T-tests), stakeholder engagement, and collaborative teamwork within a multidisciplinary setup. Interns will be expected to create reports and presentations summarizing their methodologies and findings, helping them develop professional communication skills alongside technical expertise.

Key Responsibilities:

• Analyze and manage extensive datasets

• Apply machine learning techniques and conduct EDA using Python

• Create data visualizations and dashboards with Tableau

• Collaborate with cross-functional teams to build ML pipelines

• Perform hypothesis testing and statistical analysis

• Present findings through reports and stakeholder presentations

Key Qualifications:

• Strong problem-solving and analytical thinking

• Currently pursuing any degree (open to all disciplines)

• Eagerness to learn and grow professionally

• Effective communication and collaboration skills

• Ability to work independently in a remote environment