This course aims to teach everyone the basics of programming computers using C/C++. We cover the basics of how one constructs a program from a series of simple instructions in C/C++. The course has no prerequisites and avoids all but the simplest mathematics. Will share handwritten notes pdf after every class.

With this course you will get to learn following things - Build natural, long-lasting confidence. Overcome low self-esteem. Tap into your Best Self. Use the power of NLP & Hypnosis to become supremely self-confident. Create a positive and empowering Self-image. Cultivate a strong sense of self-belief. Develop a "quiet" Confidence. Learn about the multi-layered nature of Confidence. The Success Tunnel Technique to boost confidence, self-esteem & self-belief. The Self-image Multiplier Technique. How to use Psychological Mentoring to become more confident than you can imagine. How to let go of social anxiety. How to become more confident in social situations. How to become more socially skilled.

Whether you're just starting out or already have some experience, my course offer various English Speaking courses designed to fit your needs. Take the next step in your language journey and enroll in a English Speaking course today! See you in my class :)

Hi Students, Foundation of Data Science is for complete Beginners. This course is In-depth knowledge and hands-on tools to use and work with different kinds of data. Gaining practical experience across the data science pipeline by acquiring proficiency in the data science coding language R. Foundations of Data Science is for those who work with both structured – spreadsheets and data tables – and unstructured data and who need to understand how to automate data to gain insights, contribute to strategic discussions and make data-driven decisions. With my Course you’ll gain a broad understanding of the tools and techniques used to work with data. 1. What is Data: Learn about data types, structures and frameworks 2. Interacting with Data: Understanding how data is used and how to use data 3. Where Data comes from: The processes for acquiring and sharing Data 4. Storing & Structuring Data: Working with different types of databases and data sets 5. Cleaning Data: Working with messy or incomplete data sets 6. Analyzing Data: Gaining insights with data science techniques and tools 7. Visualizing Data: Best practices and tools for data visualization and presentation 8. Machine Learning & Artificial Intelligence: How data is used by machines 9. Working as a Data Scientist: What do data scientists really do? 10. Data & Society: Ethics and the uses of data in society