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Introduction
In today’s data-driven world, businesses generate huge amounts of information every day. Effective data analytics helps uncover valuable insights, identify patterns, and make informed decisions. This leads to improved operations, better customer experiences, and targeted marketing strategies. According to Forbes, 73% of businesses recognize the significant impact of data analytics on their overall performance and competitiveness.
Scope of Course
This expert-led training provides a comprehensive exploration of data analytics, encompassing essential and advanced concepts. Participants will learn to apply various techniques and master programming languages like Python, SQL, Excel, and Tableau to transform data into actionable information. Real-world projects will enhance problem-solving abilities tailored to specific industries.
The topics covered include:
- Data Analytics Overview
- Statistics Overview
- Python for Data Analytics
- Data Analytics with Excel
- Essentials of SQL
- Data Visualization using Tableau
Program Highlights
Imparts key knowledge and skills involving
- Exploring different types of data
- Applications of Statistics
- Exploratory Data Analysis
- Data Visualization with Excel
- Essentials of SQL
- Connecting Data to Tableau
- Interactive Dashboards
- Data Blending
Career Prospects / Job Roles
The career prospects for data analytics professionals are highly promising. With the increasing importance of data-driven decision-making across industries, there is a growing demand for skilled analysts. Data analytics professionals can find opportunities in various sectors like finance, healthcare, marketing, and technology. As organisations continue to invest in data-driven strategies, the demand for data analytics professionals will only continue to grow in the future. Data Analytics professionals are hired as:
- Data Scientists
- Business Analyst
- Data Engineer
- Data Architect
Ideal For
- Statistics, mathematics, and IT / computer science students
- Students studying in science, technology, engineering, and mathematics (STEM) fields
- IT professionals who need to use data analytics
- Job seekers and working professionals looking to gain competitive advantage
- Suitable for learners with or without computer science background