Microsoft Power BI and Tableau are both powerful business intelligence tools for data visualization. Power BI is a business analytics service provided by Microsoft that can analyze and visualize data, extract insights and share it across various departments.
Data Modelling is the process of analyzing the data objects and their relationship to the other objects. It is used to analyze the data requirements that are required for the business processes. It is a process of documenting complex software system design
As data and analytics move ever closer to the core of enterprises, it’s the contemporary manager’s responsibility to both to set an example and to exert their influence to improve business performance and capability through data and analytics.
The course objective is to write powerful and dynamic Excel formulas from scratch. Automate, streamline, and completely revolutionize your workflow with Excel. Write advanced conditional, text, date and lookup functions, including XLOOKUP & Dynamic Arrays.
API is the acronym for Application Programming Interface, which is a software intermediary that allows two applications to talk to each other. Each time you use an app like Facebook, send an instant message, or check the weather on your phone, you’re using an API.
Connect web or mobile applications to databases and servers via REST APIs. Create secure and reliable REST APIs which include authentication, logging, caching, and more. Understand the different layers of a web server and how web applications interact with each other.
Understand the Basics of AI , ML, DL ( Neural Network, Computer Vision, NLP, Supervised, Unsupervised, Reinforcement ). Learn from Industry case studies of real life application of Artificial Intelligence. Learn What is Big Data and its importance.
Optimize business process,Master the General AI Framework,Implement Q-Learning,Save and Load a model,Build an Optimization Model,Implement Early Stopping,Maximize Efficiency,Maximize Revenues, Minimize Costs,Leverage AI to make the best decisions.
Learn what models are, how they work, and how they fit in the overall picture of machine learning (ML) and data science.Lots of terminology (“AI”, “deep learning”, etc.); plain and simple explanations (without the hype).
Adopt professionally tested SQL best practices. Gain theoretical insights about relational databases.Work with a sophisticated real-life database throughout the course. Get maximum preparation for real-life database management.
The course objective is to learn and practice machine learning in python and make great intuitions with diverse ML Models, powerful analysis and pinpoint predictions machine Learning model to choose for each type of problem.
Basic understanding and concepts in the world of AI in healthcare,theoretical knowledge that can help you see the big picture of AI in healthcare, coding and calculations sessions that will take you even deeper into the applications of AI in healthcare.
This course is for understanding the cloud technology concepts and gives a detailed introduction to the two largest cloud providers: Amazon Web Service (AWS), Microsoft Azure and Google Cloud Platform (GCP).Get Started with cloud now.
Understand the cybersecurity risks and the tools/techniques that can be used to mitigate those risks. We will cover the distinctions between confidentiality, integrity, and availability, introduce learners to relevant cybersecurity tools and techniques.
Learn ethical hacking, its fields & the different types of hackers.Install a hacking lab & needed software (on Windows, OS X and Linux). Hack & secure both WiFi & wired networks. Understand how websites work, how to discover & exploit web applications.
Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language.This technology is one of the most broadly applied areas of machine learnin.
Learn advanced Python features, like the collections module and how to work with timestamps.Learn to use Object Oriented Programming with classes.Understand complex topics, like decorators.Understand how to use both the Jupyter Notebook and create .py files
Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs). Predict Stock Returns and Time Series Forecasting.How to build a Deep Reinforcement Learning Stock Trading Bot.Recommender Systems & Image Recognition.
The course objective is to become an expert in Statistics, SQL, Powerbi, and problem solving,gather, organize, analyze and visualize data,use data for improved business decision-making,present information in the form of metrics, KPIs, reports.
Course objectives is to understand the Basics of AI , ML, DL ( Neural Network, Computer Vision, NLP, Supervised, Unsupervised, Reinforcement ), learn from Industry case studies of real life application of Artificial Intelligence.