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Data Structures and Algorithms in C++

22 Lessons
Beginner

The course “Data Structures and Algorithms in C++” provides a …

What you'll learn
Understanding the basics of C++ programming language and its role in implementing data structures and algorithms.
Study of fundamental data structures such as arrays, linked lists, stacks, queues, trees, and graphs in C++.
Techniques for implementing various sorting and searching algorithms in C++.
Exploration of algorithm design techniques, including divide and conquer, greedy algorithms, and dynamic programming.

Data Visualization and Storytelling for Decision Makers

18 Lessons
Beginner

Embark on a transformative journey into the realm of data-driven …

What you'll learn
Data Visualization Fundamentals: Understand the principles of data visualization and its role in conveying information and insights effectively.
The Psychology of Visual Communication: Learn how human perception is influenced by colours, shapes, and layout, allowing you to design visuals that resonate with decision makers.
Choosing the Right Visualizations: Gain insights into selecting the appropriate visualization techniques for different types of data and analytical objectives.
Crafting Data-Driven Narratives: Develop the ability to weave data into engaging stories that resonate with decision makers, fostering understanding and engagement.
Visual Design Techniques: Learn how to use colours, shapes, typography, and layout to create visually appealing and persuasive data visualizations.

Data-Driven Decision Making: Business Insights through Data Science

18 Lessons
Intermediate

Throughout this course, you will embark on a transformative journey …

What you'll learn
Foundations of Data Science for Business: Understand the fundamental concepts, terminologies, and methodologies that underpin data science and its applications in business decision-making.
Data Collection and Preprocessing Techniques: Learn how to gather, clean, and prepare data for analysis, ensuring data quality and reliability.
Exploratory Data Analysis (EDA) for Business Insights: Master techniques to uncover patterns, trends, and anomalies in data, providing a solid foundation for data-driven decisions.
Statistical Methods for Business Analysis: Explore statistical techniques to extract meaningful insights from data, enabling you to make informed decisions based on robust analyses.
Predictive Analytics and Forecasting in Business: Dive into predictive modelling to anticipate future trends, enabling proactive decision-making and strategic planning.

Database Administration and Security: Ensuring Integrity and Protection of Data

17 Lessons
Intermediate

The course “Database Administration and Security: Ensuring Integrity and Protection …

What you'll learn
Understanding the basics of database management systems (DBMS) and their components.
Study of database security principles, including authentication, authorization, and encryption techniques.
Techniques for implementing access controls and managing user privileges to protect sensitive data.
Exploration of backup and recovery strategies to ensure data integrity and disaster recovery.
Application of database monitoring and performance tuning to optimize database performance.

Deep Learning: Neural Networks and Advanced Machine Learning Models

16 Lessons
Intermediate

The “Deep Learning: Neural Networks and Advanced Machine Learning Models” …

What you'll learn
Understanding neural networks, their architecture, and how they mimic the human brain's learning process.
Study of deep learning frameworks and libraries, such as TensorFlow and PyTorch, for building and training neural networks.
Techniques for designing and optimizing various types of neural networks, including convolutional neural networks (CNNs) for image recognition and recurrent neural networks (RNNs) for sequential data.
Exploration of advanced deep learning models, such as generative adversarial networks (GANs) for image synthesis and transformer models for natural language processing.
Application of transfer learning and pre-trained models to leverage existing knowledge for new tasks.
Practice in implementing deep learning algorithms on large-scale datasets for various applications.

DevOps and Automation Mastery: Streamlining Software Delivery

19 Lessons
Intermediate

In the ever-evolving landscape of software development, the fusion of …

What you'll learn
DevOps Foundations: Understand the principles and value of DevOps in software development.
Automation Techniques: Learn to leverage automation tools to streamline tasks and eliminate errors.
Continuous Integration and Deployment (CI/CD): Master seamless code integration and automated deployment.
Infrastructure as Code (IaC): Automate infrastructure provisioning for consistency and scalability.
Configuration Management: Manage configurations systematically to reduce inconsistencies.

Digital Advertising & Marketing

22 Lessons
18.8 hours
Beginner

Welcome to the captivating realm of Digital Advertising & Marketing! …

What you'll learn
From one-off customer satisfaction surveys to brand tracking surveys that are administering on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers.
In Analytic Methods for Survey Data, statistical learners will become familiar with established methods for converting survey responses to insights that can support marketing decisions.
Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling.

Digital Advertising Mastery: Maximizing Reach and Engagement in the Digital Age

19 Lessons
Intermediate

In today’s digital landscape, digital advertising has become a crucial …

What you'll learn
Understanding the digital advertising landscape, including search engine advertising, display advertising, social media advertising, and video advertising.
Study of digital advertising strategies and best practices for creating effective campaigns that resonate with the target audience.
Techniques for defining advertising objectives, selecting the right advertising platforms, and targeting the desired audience.
Exploration of creative ad design, ad copywriting, and call-to-action elements to optimize engagement.
Application of data analytics and tracking tools to measure the performance of digital advertising campaigns.
Practice in using audience segmentation and remarketing strategies to re-engage potential customers.