Certificate in Data Analytics

Certificate in Data Analytics Course Description

Data Analysts enable businesses to maximize the value of their data assets by using Power BI.The certificate in Data Analytics teaches students to develop new analytical methods and tools by integrating the computational, statistical, and engineering techniques that form the heart of big data analytics.

Job Responsibilities

Collect and interpret data and analyse results
Create informative reports that capture key insights
Identify patterns and trends in data sets
Work with key stakeholders to create strategic plans
Define new data collection and analysis processes

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Duration

5 Months
Fee

2650.00
Format

Online/Blended
Center

All Centers

Eligibility Requirement

Participants should also have knowledge of data warehouse schema topology, programming concepts such as looping and branching, understanding of key business priorities, and familiarity with Microsoft Office apps (especially Microsoft Excel)

Job Opportunities

Data analysts
Business Intelligence professionals
Professionals who use Power BI
Professionals who manage data for decision-making
IT Managers
Data Scientists
Anybody who wants to<

Course Content

Certificate in Data Analytics

Data Analysis in Excel - Summarizing Data, Analyzing Data for Decision Making, Exchanging Data Between Various Sources, Analyzing and Presenting Complex Data Statistics for Analytics.

Introduction to Statistics and Analytics - Data Representation, Forecasting Techniques, Causality and Correlation, Hypothesis Testing, Parametric and Non-Parametric Tests Programming in Python.

Overview of Python and VSCode - Introduction to Python, pip, packages, Introduction to Python libraries, Data structures and data types in Python, Variables and Operators, Statements in Python.

Introducing Machine Learning - Managing and Understanding Data, Lazy Learning – Classification Using Nearest Neighbors, Probabilistic Learning – Classification Using Naive Bayes, Divide and Conquer – Classification Using Decision Trees and Rules, Regression Methods.