Our in-depth course in data analysis offers a broad curriculum that addresses the critical topics needed to master data analysis. The course covers advanced Excel skills, database administration and SQL querying, Python programming for data analysis and machine learning, and Power BI for efficient data visualization. Students get a comprehensive grasp of the data analysis process, enabling them to succeed in today's data-driven environment.
Pros of the Course
Enhanced Problem-Solving : By giving you the tools to recognize trends, spot anomalies, and solve complicated issues with data-driven methods, data analytics enables you to take well-informed decisions.
Improved Forecasting and Strategic Planning : Data analytics enables accurate forecasts and successful business strategies for improved forecasting and planning by analyzing patterns and trends from previous data.
Practical Application in Everyday Life : Data analytics expertise has real-world applications in daily life. Effective data organization may help with personal budgeting, and clearly communicating complicated data enhances communication abilities.
Empowered Decision-Making : Your ability to extract important insights from complicated datasets thanks to your proficiency in data analytics will help you to make well-informed judgments in a variety of industries, including business, finance, and healthcare.
Excel skills enable users to manage, modify, and analyze massive datasets with ease. It includes vital components like PivotTables and PivotCharts as well as sophisticated operations like VLOOKUP, INDEX, MATCH, and IF expressions. Advanced Excel is well known and frequently used in data analysis because of its adaptability, flexibility, and user-friendly interface.
- The basic IT functions
- Creating and using a range of name
- Locate formulas
- VLOOKUP & HLOOKUP
- INDEX & MATCH
- Analyzing Your Data
- Set up Pivot tables
- Grouping your data
- Amend Pivot Tables with new data
- Use a slicer to filter your data
- Combining slicers to more than one Pivot Table
- Using a timeline
- Organize a Pivot chart
- Reducing Your Audit Risk
- Data Recognition
- Use of Trace Precedents
- Use of Trace Dependents
- Eliminate Arrows
- Flaws checking
- Check out Formula
- Watch Window
- Enhance Your Workflow
- Set up Macro security
- Recording Macros
- How to edit Macro
- Understanding the VBA edit window
- Allow & run a Macro from the ribbon
- Saving & using a Macro-enabled Workbook
- Deleting your Macro
- Additional Topics
- Goal Seek
The fundamental tools and methods for analyzing and interpreting data are provided by mathematics and statistics, which together constitute the cornerstone of data analytics. Professionals that are proficient in mathematics may identify trends, make precise forecasts, and use cutting-edge modeling approaches.
- Linear Functions
- Linear Algebra
The fast retrieval and analysis of data from relational databases is made possible by SQL (Structured Query Language), which is a key component of data analysis. It makes it easier to analyze massive datasets accurately, and knowing SQL is essential for successful data analysis procedures. It is important to have a thorough grasp of SQL in order to deal with data efficiently and get insightful information.
- DDL and DML in MySQL and setup
- ERD Diagrams and Relational Mapping
- Data normalization
- Basic Queries
- Database Manipulation
- Table Manipulation
- Relational Algebra
- Advanced SQL - Joining, Subquery, Views
- Database Security
- Multiple Activities to Perform
Developers may build a strong portfolio displaying their coding skills and making their work available to a larger audience by using Git and GitHub. This platform provides an effective way to exchange code, cooperate with other members of the coding community, and showcase one's abilities, eventually promoting one's professional development and exposure.
Python, a popular programming language, is significant in data analysis because of its adaptability, sizable library, and simple syntax. Data analysts use Python to manage data effectively, carry out data analysis and manipulation activities, build predictive models, and produce aesthetically pleasing visualizations.
- Python Setup and What is Python?
- Data Types and Syntax
- Comparison Operators
- Python Loop
- Python Statements
- Logical Operators
- Methods and Functions
- Error and Exception Handling
- Modules Packages and libraries
- Advanced python Modules (DateTime)
- File Management
- Multiple Activities to Perform
- Multiple Projects to Build
Machine learning, a key component of artificial intelligence, enables computers to learn from data and generate predictions on their own without human interaction. By gaining important insights from large datasets and creating prediction models, it plays a significant part in data analysis.
- Data Preprocessing
- Supervised Learning
- Unsupervised Learning
- Regression Models
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- Random Forest Regression
- Topics such as
- Assessing a Regression Model
- Bias vs Variance
- Gradient Descent
- Classification Models
- Decision Tree Classification
- K-Nearest Neighbor
- Logistic Regression
- Naïve Bayes
- Random Forest Classification
- Support Vector Machines
- Additional Topics
- Assessing a Classification Model
- Gradient Boosting
- Grid Search CV
- Clustering Models
- K-Means Clustering
- Build Dashboards for Data Visualisation
- Solved Sample Code Files for easy practice
- Access to Multiple Datasets
- 7+ Real world data projects
ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are data integration processes used to extract data from various sources, transform it into a desired format, and load it into a target data warehouse or data lake for analysis and reporting. Both ETL and ELT play a crucial role in consolidating, cleaning, and preparing data for business intelligence and analytics purposes.
- Introduction to ETL/ELT
- Software Tools
- Talend Studio
- Apache Hadoop
- Apache Kafka
- Real-world data projects
Power BI is a powerful data visualization tool that enables analysts to create interactive dashboards, reports, and visualizations. With its user-friendly interface and robust features, Power BI empowers users to transform raw data into insightful and visually engaging representations. Analysts can easily explore data, identify trends, and communicate findings effectively, making Power BI an indispensable tool for data-driven decision-making.
- Introduction to Power BI
- Overview of Power BI
- Advantages of Power BI
- Power BI components
- Power BI service vs Power BI desktop
- Data Sources and Connections
- Data sources overview
- Connecting to different data sources
- Working with data in Power BI
- Data Transformation and Modeling
- Data transformation and cleaning
- Data modeling
- Creating relationships between data tables
- Basic visualization types
- Customizing visualizations
- Working with visuals and filters
- DAX Functions
- Introduction to DAX functions
- DAX formulas and expressions
- Aggregating and summarizing data with DAX
- Sharing and Collaboration
- Sharing and publishing reports
- Managing access to reports
- Collaboration with Power BI
- Advanced Topics
- Advanced data modeling
- Custom visuals and extensions
- Power BI embedded
- Case Studies and Hands-On Projects
- Real-world case studies
- Hands-on projects with Power BI
Tableau is a user-friendly business intelligence and data visualisation application that creates interactive visualisations from data to help organisations make decisions based on that data.
- Tableau Installation
Installing Tableau on your computer will allow you to undertake data analysis.
- Tableau UI
You will learn how to utilise the Tableau user interface to do research and create data visualisations.
- Tableau UI Components
Utilising elements for building visualisations, including as sheets and legends, using Tableau UI components.
- Tableau Marks Card
Manages how data points look in a display.
- Tableau Functions
Understanding built-in data manipulation algorithms using Tableau Functions.
- Filters in Tableau
Using tools for data focus and visualisation refinement, such as filters in Tableau.
- Forecasting with Tableau
Utilise automated predictions to forecast future data patterns when forecasting using Tableau.
Customising an interactive visualisation by working with dynamic values.
The process for using quantitative data in calculations.
Data categorization and grouping using categorical variables.
Project In Tableau
- House Data Dashobard - Project I
- Jobs Data Dashboard - Project II
Learn Tkinter, a well-known GUI toolkit, to create one-of-a-kind bespoke programs with eye-catching interfaces. Additionally, find out how to use Python's integrated SQLite database to quickly save and retrieve data within your programs, improving their usability and usefulness. You gain the knowledge and abilities necessary to develop data-driven, interactive apps that match your unique needs thanks to this add-on module.
Skills You Will Gain
The students will acquire following set of skills after completing this Training Course.
Data Visualization : Master the skill of using interactive visualizations, charts, and graphs to display complicated data in a way that is visually appealing and ensures stakeholders can understand and digest the information with ease.
Data Mining : Learn how to use methods like clustering, classification, and association analysis to extract hidden patterns, trends, and insights from huge datasets, allowing decision-making based on insightful data findings.
SQL and Database Querying : Gain proficiency in relational database extraction, manipulation, and analysis using SQL (Structured Query Language), improving data analysis procedures and boosting data-driven insights.
Programming Proficiency : Become proficient in programming languages like Python to automate activities, analyze data more effectively, streamline workflows, and produce more significant outcomes.
Business Acumen : Develop a thorough grasp of business principles and subject-matter expertise, coordinating data analysis activities with corporate goals, and making data-driven suggestions that promote company success.
Business Intelligence Analyst
Powe BI Analyst
Market Research Analyst
Data Quality Analyst
Predicting Cancer Malignant or Benign
Predicting Stock Prices
Wine Quality Prediction
Power BI Projects
Participants will receive certificates from Future Connect Training to mark their success and the priceless information they have learned after completing the training program.
This course includes:
- Learn Excel (Basic, Intermediate, Advanced)
- Learn Python, SQL (Database)
- Learn Machine Learning Skills
- Learn some popular software such as VS Code, XAMPP/MAMPP, Anaconda
- Learn some popular libraries such as Pandas, Numpy and ScikitLearn
- Creative Activities, Lectures and more
- Masters level Course Content with Hands-on Training
- Multiple Projects to test your skills upon
- Join the leading Industry with over 20 billion Pounds of investment
- Online Practical Training
- Flexible Payment Structure
- CV Support