Simplilearn
Description
About The Course:
This Data Analyst Master’s Program, in collaboration with IBM, will transform you into a data analytics expert. In this course, you will learn the latest analytics tools and techniques, how to work with SQL databases, the languages of R and Python, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment.
Outline
Course Key Features:
- Exclusive hackathons and live interaction with IBM leadership
- Live masterclasses and Ask Me Anything sessions from IBM experts
- 8X higher live interaction with live online classes by industry experts
- Capstone and 20+ real-life Data Science projects built on data sets from different industries such as Banking, eCommerce, Technology, and Manufacturing
- Top-notch curriculum with integrated labs
Certificate: Upon completion of this Master’s Program, you will receive certificates from IBM and Simplilearn in the Data Analyst courses in the learning path. Upon program completion, you will also receive an industry-recognized Master’s Certificate from Simplilearn.
Who Should Enroll?
A career as a data analyst requires a foundation in statistics and mathematics. Aspiring professionals of any educational background with an analytical frame of mind are best suited to pursue the Data Analyst Master’s Program, including:
- IT professionals
- Banking and finance professionals
- Marketing managers
- Supply chain network managers
- Beginners in the data engineering domain
- Students in UG/ PG programs
Takeways
Course Takeaways:
- Understand essential statistical concepts, including measures of central tendency, dispersion, correlation, and regression
- Master SQL concepts such as Universal Query Tool and SQL command
- Write your first Python program by implementing concepts of variables, strings, functions, loops, and conditions
- Understand the nuances of lists, sets, dictionaries, conditions and branching, objects, and classes in Python
- Work with data in Python, including reading and writing files, loading, working, and saving data with Pandas
- Learn how to interpret data in Python using multi-dimensional arrays in NumPy, manipulate DataFrames in Pandas, use SciPy library of mathematical routines, and execute machine learning using Scikit-Learn
- Perform data analytics using popular Python libraries
- Gain insights on several data visualization libraries in Python, including Matplotlib, Seaborn, and Folium
- Gain an in-depth understanding of the basics of R, learning how to write your own R scripts
- Master R programming and understand how various statements are executed in R
Paid Search & App Campaigns Executive 
Hyderabad
