Introduction: What do we mean by Data Science?

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Data Science: Python for Engineers - Part II

Explores data wrangling, numerical data handling, and scientific visualization using Python for engineers.

Machine Learning Basics

Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.

Data Science with Python: Numpy Basics

Introduces the basics of Numpy, a numerical computing library in Python, covering advantages, memory layout, operations, and linear algebra functions.

Data Analysis to AI and ML, Social Media

Explores the evolution from data analysis to AI and ML, emphasizing big data, machine learning, and social media interaction.

Deep Learning: Data, Models, and Challenges

Provides an overview of deep learning concepts, focusing on data, model architecture, and challenges in handling large datasets.

Data Science with Python

Covers Python basics, Pandas, data manipulation, visualization, and machine learning.

Knowledge Representation: Semantics and Data Structures

Explores knowledge representation, data structures, semantics, and the challenges of searching for data on the web.

Google Analytics 4: Understand & set up GA4

Introduces Google Analytics 4 and guides on setting it up for WordPress websites, emphasizing key differences and event tracking.

Handling Data: Intro to Pandas

Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.

Advanced Spark Optimization Techniques: Managing Big Data

Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.