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Linkedin courses python9/13/2023 ![]() ![]() If you intend to complete this path, I'd also recommend learning Python syntax on Codecademy, the top Python course according to the data. The one gripe I have with this path is that the Python course at the end already assumes Python experience, but nowhere in the path is there a Python syntax course. There is some overlap with the statistics and visualization content, but for a beginner, this can only reinforce your newly acquired analytics skills as a beginner. You can acquire many in-demand skills from the data analyst path on Linkedin Learning. Detecting, preventing, and fixing errors.Creating custom calculations and fieldsĬourse 11 SQL: Data Reporting and AnalysisĬourse 12: R Essential Training: Wrangling and Visualizing DataĬourse 13 Data Cleaning in Python Essential Training.Cross-Industry Standard for Data Mining (CRISP-DM).Problems and solutions you'll face with data. ![]() One benefit to this course series over Google's is the inclusion of statistics modules, which is excellent for learners that would like to strengthen their math for analytics.Ĭourse 1: The Non-Technical Skills of Effective Data ScientistsĬourse 3: Data Fluency: Exploring and Describing DataĬourse 4: Learning Data Analytics: 1 FoundationsĬourse 5: Learning Data Analytics Part 2: Extending and Applying Core KnowledgeĬourse 6: Excel Statistics Essential Training: 1Ĭourse 7: Predictive Analytics Essential Training: Data Mining The course path is similar in scope to that of Google's listed above, but focusing on Microsoft products, namely Excel and Power BI. The data analyst learning path from Linkedin Learning in a collection of courses organized in a way that provides you with a well-rounded education. Those looking for broad exposure to many data analytics tools, but with more of a focus on Microsoft products So, depending on your background, you may well finish the course series quicker than advertised.Įnroll in the Google Data Analytics Professional Certificate Some learners report they completed the entire Specialization in under a month. The curriculum is divided into "courses," but some of the content can be completed far shorter than a typical Coursera course.
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