Python Course For Data Science
What will I learn?
Improve your Business Intelligence skills (Ntlafatsa tsebo ea hau ea Business Intelligence) with our concise, high-quality Python Course for Data Science (Khoebo ea Python bakeng sa Data Science ea boleng bo holimo). Learn essential data cleaning techniques (Ithute mekhoa ea bohlokoa ea ho hloekisa data), including handling duplicates and outliers (ho kenyeletsa ho sebetsana le likopi le lintho tse sa tloaelehang), and dive into sales performance analysis with regional and product category insights (ho kenella tlhahlobisong ea ts'ebetso ea thekiso ka leseli la libaka le lihlahisoa). Gain proficiency in data loading, preprocessing, and key metrics calculation (Fumana boiphihlelo ba ho kenya data, ho e lokisa esale pele, le ho bala lipalo-palo tsa bohlokoa). Enhance your ability to communicate insights effectively using Jupyter Notebook (Ntlafatsa bokhoni ba hau ba ho fana ka leseli ka katleho u sebelisa Jupyter Notebook), and uncover actionable recommendations to boost sales strategies and inventory management (fumana likhothaletso tse ka nkeloang khato ho matlafatsa maano a thekiso le taolo ea thepa).
Apoia's Unique Features
Develop skills
Enhance your practical skills as listed below
Master data cleaning: Remove duplicates, normalize, and treat outliers effectively (Ithute ho hloekisa data: tlosa likopi, o tloaetse, o phekole lintho tse sa tloaelehang ka katleho).
Analyze sales data: Perform regional, product, and time series sales analysis (Hlahloba data ea thekiso: Etsa tlhahlobo ea thekiso ea libaka, lihlahisoa le linako).
Preprocess data: Convert types, handle missing values, and load CSVs with Pandas (Lokisa data esale pele: Fetola mefuta, sebetsana le boleng bo sieo, 'me u kenye li-CSV ka Pandas).
Calculate key metrics: Determine total revenue, regional revenue, and average units sold (Bala lipalo-palo tsa bohlokoa: Fumana chelete eohle e kenang, chelete e kenang ea libaka, le karolelano ea lihlahisoa tse rekisitsoeng).
Communicate insights: Structure findings and present using Jupyter Notebook (Fana ka leseli: Hlophisa liphumano 'me u fane ka tsona u sebelisa Jupyter Notebook).
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can adjust the chapters and workload.
- Choose your starting chapter
- Add or remove chapters
- Alter the total course workload
Examples of chapters you can include
You'll be able to generate additional chapters similar to the examples below
This is a free course focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but provides practical and relevant knowledge for your career.