Data Analytics Course
Acquire industry-standard skills to advance your career, and optimize business performance with data analytics.
Why Data Analysis
A data analytics course teaches how to analyze large datasets with statistical & machine learning techniques. It helps individuals understand how businesses make data-driven decisions. Topics include data visualization, predictive analytics, and more. The course includes lectures, exercises, and project work. After completion, individuals will be proficient in data analytics and can add value to their organizations.
Why Should I Learn Digital Marketing?
"It is impossible for a man to learn what he thinks he already knows."
There are several reasons why learning data analytics is becoming increasingly important in the modern world.
Firstly, data is being generated at an unprecedented rate, and organizations are looking for ways to better understand and use it to gain a competitive edge.
Secondly, data analytics helps identify patterns and insights that may not be immediately apparent, allowing organizations to make informed decisions based on data rather than gut instinct.
Thirdly, data analytics can help organizations identify areas of waste, reduce costs, and optimize processes.
Fourthly, data analytics skills are in high demand in almost every industry, which makes them valuable skills to have for career advancement.
Lastly, data analytics is a rapidly growing field with endless opportunities for learning and developing new skills.
Course Outline
Introduction to Data Analytics
This Data Analytics course teaches you skills in Excel and Python to perform analyses and gain insights. You'll learn data collection, cleaning, visualization, interpretation, regression analysis, and predictive modeling. Real-world examples from marketing, finance, and healthcare will solve complex problems. Apply concepts to your work and personal life. Start becoming a data analyst today!
Basic to Advance Microsoft Excel
Advanced Microsoft Excel skills are key in many industries, enabling efficient data manipulation and analysis. Key skills include creating formulas and functions, using pivot tables and macros, managing large datasets with filtering and conditional formatting, and developing professional reports and dashboards. Achieving these skills takes time and practice but can lead to career growth and more effective data analysis.
PowerBI
To master Power BI, learn data modeling, visualization, DAX expressions, Power Query, Power BI Service, Desktop, and Excel Integration. These essential skills will help transform data, create informative graphics, and provide insights that drive business success.
MySQL
MySQL is an open-source database system used in data analytics. Key MySQL skills for data analytics include database design, SQL, data modeling, performance tuning, and data integration. It's important to set up a database with a good schema and write SQL queries to extract and transform data. Data models are helpful in visualizing data relationships and creating structures, while optimizing MySQL queries improves performance. Integration of data from various sources and formats using MySQL is also crucial.
Python Programming
To excel in data analytics, mastering Python is essential. This includes basic coding, data structures/algorithms, pandas, matplotlib/seaborn, statistics, inferential statistics, data cleaning, machine learning (linear regression, decision trees, SVMs, random forests), NLP, and cloud-based tools like AWS/Azure. With these skills, individuals can build better data models and provide valuable insights for data-driven businesses.