Page 148 - Ai_V3.0_c11_flipbook
P. 148
• Statistics: Science of collecting, analysing, and interpreting data, used
in science, engineering, and social sciences for making data-driven
decisions.
• Signal Processing: Analysis and interpretation of signals, such as
audio and video data, used in telecommunications, medical imaging,
and control systems.
• Big Data: Management and analysis of large and complex datasets,
facilitated by technologies like Hadoop and Spark, applied across
industries for extracting insights and value from data.
Your Professional Toolkit
In addition to learning the requisite skills, AI practitioners should become familiar with prominent AI tools, platforms,
and programming languages. Few important tools and frameworks are as follows:
• Python is a versatile programming language with pre-built libraries for advanced and scientific computing.
• R is a computer language used for data collecting, organising, and analysing, with applications in machine learning
and statistics.
• Java is a commonly used language in AI to develop intelligent programs, neural networks, and machine learning
solutions.
• C++ is flexible and object-oriented language, making it ideal for procedural programming and hardware manipulation
in AI.
• TensorFlow is an open-source machine learning framework that provides tools and libraries for building advanced
AI applications.
• SciPy is an open-source Python library, used for solving scientific and mathematical problems. It helps users to
manipulate and visualise data using various commands.
• NumPy is a Python-based package used for scientific computing and advanced mathematical operations while
managing massive data set.
Aspiring AI professionals can prepare themselves for success in this dynamic and quickly growing sector by learning
the necessary technical skills and tools. Whether you want to develop AI algorithms or apply AI solutions in real-world
applications, establishing a solid foundation of skills, and expertise is essential for pursuing fascinating career options
in artificial intelligence.
Traits Required for an AI Professional
If you are an aspiring AI professional, it's useful to have the following general characteristics:
• Be Curious: Curiosity is essential for comprehending the business problems, analysing the data, and seeking potential
data applications.
146 Touchpad Artificial Intelligence (Ver. 3.0)-XI

