edX - Accelerator Program in Business Analytics and Data Science 

Self-paced: Introduction to Analytics

Get introduced to the fundamental concepts of analytics at your own pace,this course covers the importance of analytics in business, different types of analytics (descriptive, diagnostic, predictive, and prescriptive), and the scientific methods used to implement analytics effectively

Python Programming

This course covers the Basics of Python, including installation, syntax, data structures, file handling, and web scraping

Basic Mathematics

This course provides the foundational knowledge in mathematics crucial for data analytics,topics include linear algebra (vectors, matrices),calculus (differentiation, integration), and basic probability and statistics (mean, median, mode, variance, standard deviation)

Project: Pipeline

This hands-on project focuses on building a simple ETL (Extract, Transform, Load) pipeline. You'll learn to scrape data, clean and transform it according to requirements, and store the cleaned data efficiently for further analysis

Excel

Master both basic and advanced features of MS Excel for data handling, summarization, and visualization,this course includes navigation, data manipulation using functions, and the creation of complex charts and pivot tables

Database

Gain a deep understanding of both SQL and NoSQL databases,this course covers essential SQL commands, data manipulation, advanced queries, and relationships

Project: Manipulation from SQL

This project emphasizes data manipulation using SQL and Excel. You'll perform various SQL operations to extract, transform, and load data, followed by advanced data manipulation and visualization in Excel to gain actionable insights

Python for Data Analysis

Master data analysis using Python's powerful libraries, Pandas and NumPy. This course covers data handling, manipulation, advanced indexing, and performing complex operations on multiple datasets to derive meaningful insights

Data Analysis and Visualization using Excel

Learn how to effectively analyze and visualize data using Excel. This course covers the creation of dashboards, data visualization techniques, and the use of Excel's powerful data analysis tools to gain insights and make data-driven decisions

Machine Learning

Explore the fundamentals of machine learning, covering both supervised and unsupervised techniques,topics include regression, classification, clustering, and model evaluation, with practical applications and industry-specific examples

Deep Learning

This course introduces deep learning concepts, including neural networks, forward and backward propagation, and gradient descent. You'll also learn to build and evaluate neural networks using TensorFlow and Keras, focusing on practical applications and model optimization

Capstone

The Capstone project allows you to apply the knowledge and skills acquired throughout the program