Data Science vs Data Analytics vs Artificial Intelligence
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About this Course:
Data science involves statistical techniques while AI involves algorithmic techniques. Data science looks for hidden patterns for decision making whereas AI relies on intelligent reports for making decisions. Medium level processing of data is involved for data manipulation, on the other hand manipulation of data involves high order processing of data. Data science is represented by statistical graphical models while models that employ network nodes for imitating human cognitive processes are involved in AI.
- What is Data Science and Key things
- What is Data Analytics and key things
- What is machine learning and key things
- What is major difference in the topics
- Jr. Data Analysts
- People looking to move in the Data Science Field
- Business executives looking for a more Data Driven approach to understand company needs
- No Prerequisites for this course
|Subjects||Business Productivity, IT Ops & Management|
|Learning Style||Self-Paced Learning|
|Course Duration||1 Hour|
(Data Science Enthusiast)
Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.
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