Data Insight
Oct 1, 20213 min
Updated: Nov 14, 2021
Advanced Business Analytics Specialization (University of Colorado)
Applied Data Science with Python (University of Michigan)
Data Analyst Professional Certificate (IBM)
Data Science on Microsoft Azure Using Python Programming (FutureLearn)
Data Science Professional Certificate (IBM)
Data Science Specialization (John Hopkins University)
Data Science with Python Certification Training (Edureka)
Data Scientist Career Path (Codecademy)
Data Scientist Nano Degree Program (Udacity)
Data Scientist Program (Data Insight)
Deep Learning Specialization (DeepLearning.AI)
Machine Learning Course (Andrew Ng @ Stanford)
Machine Learning, Data Science and Deep Learning (Udemy)
Machine Learning Specialization (University of Washington)
Master Python for Data Science (LinkedIn Learning)
Mathematics for Machine Learning (Imperial College London)
Programming with Python (Brilliant)
Python for Everybody Specialization (University of Michigan)
Python Machine Learning Certification Training (Edureka)
Reinforcement Learning Specialization (University of Alberta)
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The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results.
The problems faced by decision makers in today’s competitive business environment are complex. Achieve a clear competitive advantage by using data to explain the performance of a business, evaluate different courses of action, and employ a structured approach to business problem-solving.
This course will help you to gain new insights into your data. You will learn to apply data science methods and techniques, and acquire analysis skills.
Course highlights
Conduct an inferential statistical analysis
Enhance a data analysis with applied machine learning
Discern whether a data visualization is good or bad
Analyze the connectivity of a social network
Unlock your potential in data analytics with this Data Analyst Professional Certificate from IBM. Build job-ready skills for an in-demand career as a data analyst. No degree or prior experience required to enrol in this program.
The program will allow you to demonstrate proficiency in using spreadsheets and utilizing Excel to perform a variety of data analysis tasks like data wrangling and data mining. Create various charts and plots in Excel & work with IBM Cognos Analytics to build dashboards. Visualize data using Python libraries like Matplotlib.
You will develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services. Describe data ecosystem and Compose queries to access data in cloud databases using SQL and Python from Jupyter notebooks.
This ExpertTrack on the FutureLearn Platform offers you the chance to discover Python programming fundamentals while understanding cloud computing and its applications in data science. You will grow your knowledge in Microsoft Azure as you begging to model data using Azure.
You will also learn key skills in applying queries, modifying data, creating data visualizations using a range of market-leading tools.
Lauch your career in Data Science & Machine Learning with a Professional Certificate from IBM.
With this program you will build data science skills, learn Python & SQL, analyze & visualize data, build machine learning models. No degree or prior experience required to enrol.
This course will teach you what data science is, the various activities of a data scientist’s job, and methodology to think and work like a data scientist. You will learn how to import and clean data sets, analyze and visualize data, and build and evaluate machine learning models and pipelines using Python.
You will develop hands-on skills using the tools, languages, and libraries used by professional data scientists and apply various data science skills, techniques, and tools to complete a project and publish a report.
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