Overview of Analytics Course in Newcastle

Newcastle is a vibrant city located in the northeast of England with a rich history and culture, as well as a thriving business community. With the rise of big data, there is an increasing demand for professionals who can make sense of vast amounts of data and help organizations make informed decisions. For anyone interested in pursuing a career in the field of analytics, Newcastle offers a range of courses and programs that can help you develop the skills and knowledge you need to succeed. One of the most popular analytics courses in Newcastle is the Master of Analytics program offered by Newcastle University Business School. This program is designed to give students a deep understanding of the field of analytics, including data analysis, visualization, and predictive modeling. The program covers a broad range of topics, from statistical methods to machine learning, and emphasizes the practical application of these skills to real-world business problems. Another option for people interested in analytics courses in Newcastle is the Professional Certificate in Business Analytics offered by the University of Newcastle. This program is designed for professionals who want to deepen their knowledge of data analysis and gain practical skills that they can apply immediately in their work. The program covers a range of topics, including data visualization, statistical analysis, and predictive modeling. For those who are just starting their careers in analytics or who want to gain a foundational understanding of the field, the Certificate IV in Data Analytics offered by TAFE NSW is a great option. This program covers the basics of data analysis, including data collection, cleansing, and visualization. It also covers basic statistical methods and introduces students to the software tools commonly used in the field of analytics, such as Microsoft Excel and Tableau. Many companies in Newcastle are actively recruiting professionals with analytics skills, and the job market for data scientists and analysts is expected to continue growing in the coming years. Graduates of analytics courses in Newcastle are well-positioned to take advantage of these opportunities, with many finding work in a range of industries, including finance, healthcare, and government. In addition to the academic programs mentioned above, there are also a variety of professional organizations and networking opportunities available in Newcastle for people interested in analytics. These include the Newcastle Data Analytics Network, which hosts regular events and workshops for people interested in data analysis and visualization. There are also several meetup groups focused on data science and analytics, as well as a thriving community of professionals in the region who are happy to share their knowledge and expertise. In conclusion, if you are interested in pursuing a career in analytics, Newcastle is an excellent place to start. With a range of academic programs, professional organizations, and networking opportunities available, there are plenty of resources to help you develop the skills and knowledge you need to succeed in this exciting field.
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Course Duration

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Internship

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Live Training

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Career Assistance

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Skillfloor Course Training Process
Skillfloor Course Training Process

Internship Certificate

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Completing this Analytics Course certifies your proficiency in data analysis, statistical methods, and essential analytics tools. This certification shows you can transform raw data into actionable insights, improving decision-making in various business contexts. It indicates your understanding of data visualization, predictive modelling, and data-driven strategy development, providing you with the skills to excel in analytics. This credential reflects your dedication to continuous learning and commitment to leveraging data for strategic advantage.

Analytics Tools Covered

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Why Choose SKILLFLOOR for Analytics in Newcastle?

Why Course Training in Skillfloor

Syllabus

- Overview of data analysis and its importance in business

- Types of analytics: Descriptive, Predictive, Prescriptive

- Role of data in decision-making processes

- Introduction to common tools: Tableau, PowerBI, Excel

- Ethical considerations in data collection and analysis

- Data sources: Primary and secondary data

- Data collection methods (surveys, web scraping, databases)

- Data cleaning techniques (handling missing values, outliers)

- Data transformation and feature engineering

- Data storage concepts (structured vs. unstructured data)

- Descriptive statistics: Mean, median, mode

- Data visualization basics (histograms, scatter plots)

- Identifying data patterns and trends

- Outlier detection and handling methods

- Correlation and causation analysis

- Inferential statistics and probability theory

- Hypothesis testing (t-tests, chi-square tests, ANOVA)

- Measures of central tendency and variability

- Confidence intervals and margin of error

- Regression analysis: Linear and logistic regression

- Principles of effective data visualization

- Types of charts and their uses (bar, line, pie, heatmaps)

- Designing dashboards for different audiences

- Interactive visualization techniques

- Data storytelling for impactful presentations

- Time series analysis and forecasting methods

- Clustering and segmentation analysis

- Decision trees and classification techniques

- Introduction to machine learning in business analytics

- Model evaluation and selection

- Basics of SQL for data manipulation

- Creating databases and relationships

- Aggregating data with SQL (GROUP BY, JOIN)

- Data modeling for business intelligence (star and snowflake schemas)

- Case study: Building a business model with SQL

- Connecting and preparing data in Tableau

- Creating basic visualizations (charts, maps)

- Advanced Tableau functions (LOD calculations, table calculations)

- Building interactive dashboards and stories

- Publishing and sharing visualizations on Tableau Server/Online

- Introduction to PowerBI workspace and components

- Data import and transformation with Power Query

- Data modeling and relationships in PowerBI

- Creating and customizing visualizations

- Publishing and collaborating on PowerBI Service

- Selecting a real-world dataset for analysis

- Defining business questions and objectives

- Conducting data analysis and visualization

- Presenting findings in a comprehensive dashboard

- Peer review and feedback on project

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