Data Science with AI

Description

Data science training program you will learn how to represent, maintain, and process large data sets utilizing innovative techniques and methodologies, as well as modern methods and tools for visual exploration. The course's core modules teach the fundamental skills of a data scientist, such as using machine learning, managing big data sets, and creating compelling visualizations. The obtained skills will be useful for business applications, industrial applications, and scientific data investigation.

Course Objective

Data science soon will be a must-have profession for every company looking to fully capitalize on the data it collects. There will be an expanding need for people who have the required skills in mathematics, statistics, computer science, business expertise, and the ability to apply developing technology to practical problems.

Expertise in

Learning outcomes

Data Manipulation and Cleaning:

Mastering techniques to handle missing values, outliers, and inconsistencies.
Proficiency in data cleaning and preprocessing using tools like Python (Pandas, NumPy) and R.

Data Exploration and Visualization:

Understanding data distribution, relationships, and trends.
Creating effective visualizations using libraries like Matplotlib, Seaborn, and Plotly.

Statistical Analysis:

Applying statistical methods to draw meaningful insights from data.
Using statistical software like SPSS or R for hypothesis testing, correlation analysis, and regression analysis.

Machine Learning:

Building predictive models using algorithms like linear regression, decision trees, random forests, and support vector machines.
Implementing machine learning algorithms using Python libraries like Scikit-learn.

Deep Learning:

Perform financial forecasting using advanced analytical methods.
Use data visualization to present financial insights to stakeholders.

Big Data Technologies:

Working with large datasets using tools like Hadoop, Spark, and Apache Flink.
Leveraging cloud platforms like AWS, Azure, and GCP for scalable data processing.