|
via Udemy |
Go to Course: https://www.udemy.com/course/complete-data-analysis-course-for-absolute-beginners-2020/
I recently explored a comprehensive data science course available on Coursera that I highly recommend for aspiring data professionals. Taught by an instructor with over 15 years of experience in Data Science and Big Data, this course offers an invaluable blend of practical skills and theoretical knowledge, making it ideal for those looking to elevate their data literacy from beginner to expert level. One of the standout features of this course is lifetime access to all course materials, allowing learners to revisit content at their own pace. Although Coursera doesn't specify a refund policy, Udemy, which often offers similar courses, provides a 30-day refund guarantee, adding an extra layer of confidence for students. Content Breakdown: The curriculum is rich and hands-on, covering vital tools like SQL, Excel, R, and Python. You will start by mastering SQL queries practically and learn how to execute them across different databases such as Oracle and MySQL. The course emphasizes real-world applicability by engaging students with numerous projects and case studies, including data analysis on datasets like Bank Marketing, Uber demand-supply analysis, investment trend evaluation, and telemarketing data analysis. Students will learn to perform Exploratory Data Analysis (EDA), derive meaningful insights, and create compelling visualizations like bar charts and box plots. The course introduces how to integrate R and Python with databases, enabling you to write SQL commands directly within these programming environments. Furthermore, you'll learn to set up your own databases on your laptop, import/export data, and analyze real datasets. Practical Impact: What sets this course apart is its focus on application. The inclusion of case studies offers learners experience with real business scenarios, such as identifying creditworthy customers, analyzing Uber demand gaps, understanding global investment trends, and predicting customer behaviors for telemarketing campaigns. These projects enhance your capability to translate data insights into strategic decisions. Recommendation: Whether you're a beginner eager to enter the data science realm or a professional looking to sharpen your skills, this course is an excellent choice. Its comprehensive coverage, practical projects, and expert-led instructions make it a valuable investment. The lifetime access ensures you can learn at your own pace, revisiting modules whenever needed. In summary, if you aspire to become proficient in SQL, Excel, R, and Python for data analysis and visualization, this course will provide you with the necessary tools and experience to excel in the data-driven world. I highly recommend enrolling to transform your data skills and open new career opportunities.
*Lifetime access to course materials. Udemy offers a 30-day refund guarantee for all courses**Taught by instructor with 15+ years of Data Science and Big Data Experience*The course is packed with real life projects examples and has all the contents to make you Data Literate.Get Transformed from Beginner to Expert. Become expert in SQL, Excel and R programming.Start using SQL queries in Oracle , MySQL and apply learning in any kind of databaseStart doing the extrapolatory data analysis ( EDA) on any kind of data and start making the meaningful business decisions.Start writing simple to the most advanced SQL queries.Integrate R and Python with Database and execute SQL command on them for data analysis and Visualizations.Start making visualizations charts - bar chart , box plots which will give the meaningful insightsLearn the art of Data Analysis , Visualizations for Data Science ProjectsLearn to play with SQL on R and Python Console.Integrate RDBMS database with R and PythonCreate own database in your laptop/Desktop - Oracle and MySQLImport and export data from and to external files.Real world Case Studies Include the analysis from the following datasets1. Bank Marketing datasets ( R ) 2. Identify which customers are eligible for credit card issuance ( R)3. Root Cause Analysis of Uber Demand Supply Gap ( R) 4. Investment Case Studies: To identify the top 3 countries and investment type to help the Asset Management Company to understand the global trends ( EXCEL) 5. Acquisition Analytics on the Telemarketing datasets: Find out which customers are most likely to buy future bank products using tele-channel. ( EXCEL) )6. Market fact data.( SQL)