Certified Data Analysis Training Course
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Download pdf| No upcoming Schedule available for this course. | Register |
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| Did you know you can also choose your own preferred dates & location? click the register button. | Register |
| No upcoming Schedule available for this course. | Register |
|---|---|
| Did you know you can also choose your own preferred dates & location? click the register button. | Register |
Course Overview
This Certified Data Analysis Training Course is designed to equip participants with practical knowledge and hands-on skills in data analysis, visualization, and storytelling. It covers the core concepts of data handling, statistical analysis, and transforming insights into compelling data-driven narratives. Participants will gain proficiency in using analytical tools and methods to support data-driven decision-making in a variety of industries.
Why Select This Training Course?
By the end of this course, participants will be able to:
- Understand and apply foundational concepts in data analysis and statistics
- Perform exploratory data analysis and interpret key statistical measures
- Create meaningful data visualizations and dashboards
- Communicate insights clearly through data storytelling techniques
- Use tools like Excel, Python, Power BI or Tableau to analyze and present data
Who Should Attend?
This course is ideal for:
- Business analysts, marketing analysts, and financial analysts
- Data professionals seeking to enhance analytical skills
- Recent graduates with a background in business, mathematics, or computer science
- Mid-level managers and team leaders aiming to improve data-driven decision-making
- Anyone interested in transitioning into a data analysis role
Course Syllabus
Module 1: Introduction to Data Analysis
- What is data analysis? Importance and application in modern industries
- Types of data: Structured vs. Unstructured
- Introduction to data analytics lifecycle
- Overview of key tools: Excel, Python, SQL, Tableau/Power BI
Module 2: Data Collection and Cleaning
- Data sources and data types (quantitative vs qualitative)
- Data collection methods and techniques
- Data wrangling: cleaning, transforming, and preparing datasets
- Handling missing data and outliers
- Introduction to Python Pandas / Excel for data cleaning
Module 3: Data, Statistics, and Statistical Analysis
- Descriptive statistics: mean, median, mode, range, variance, standard deviation
- Inferential statistics: hypothesis testing, confidence intervals, p-values
- Correlation vs. causation
- Regression analysis (linear & logistic)
- ANOVA and Chi-square tests
- Hands-on with Python (SciPy, statsmodels) / Excel / R
Module 4: Exploratory Data Analysis (EDA)
- Introduction to EDA: objectives and approach
- Identifying patterns, trends, and anomalies
- Visual EDA using histograms, boxplots, scatter plots, heatmaps
- Feature selection and dimensionality reduction (basic PCA)
Module 5: Data Visualization
- Principles of effective data visualization
- Choosing the right chart: bar charts, line graphs, pie charts, scatter plots, etc.
- Dashboard design and user experience
- Hands-on with Tableau / Power BI / Python (Matplotlib, Seaborn)
Module 6: Data Storytelling
- The art of telling stories with data
- Understanding audience and context
- Structuring the narrative: beginning, insights, call to action
- Combining visuals and narrative for maximum impact
- Case studies and real-world examples
Module 7: Capstone Project
- End-to-end data analysis project:
- Define the problem
- Collect and clean data
- Perform analysis and visualizations
- Develop a data story and present findings
- Peer review and feedback session
- Tools Used (Depending on Track Chosen)
- Excel/Google Sheets – Basic data handling and statistics
- Python – Pandas, Matplotlib, Seaborn, SciPy
- Tableau / Power BI – Dashboards and storytelling
- SQL (Optional) – Data querying
FAQs
4 simple ways to register with RCADEMY:
- Website: Log on to our website www.rcademy.com. Select the course you want from the list of categories or filter through the calendar options. Click the “Register” button in the filtered results or the “Manual Registration” option on the course page. Complete the form and click submit.
- Telephone: Call +971 58 552 0955 or +44 20 3582 3235 to register.
- E-mail Us: Send your details to [email protected]
- Mobile/WhatsApp: You can call or message us on WhatsApp at +971 58 552 0955 or +44 20 3582 3235 to enquire or register.
Believe us; we are quick to respond too.
Yes, we do deliver courses in 17 different languages.
Our course consultants on most subjects can cover about 3 to maximum 4 modules in a classroom training format. In a live online training format, we can only cover 2 to maximum 3 modules in a day.
Our public courses generally start around 9 am and end by 5 pm. There are 8 contact hours per day.
Our live online courses start around 9:30am and finish by 12:30pm. There are 3 contact hours per day. The course coordinator will confirm the Timezone during course confirmation.
A valid RCADEMY certificate of successful course completion will be awarded to each participant upon completing the course.
A ‘Remotely Proctored’ exam will be facilitated after your course. The remote web proctor solution allows you to take your exams online, using a webcam, microphone and a stable internet connection. You can schedule your exam in advance, at a date and time of your choice. At the agreed time you will connect with a proctor who will invigilate your exam live.
