Certified Ekasi Data Science Technician
Technology and Data
Advanced
Certified Ekasi Data Science Technician
Dive into the world of data science, covering programming, statistics, machine learning algorithms, and model deployment. Learn to build predictive models that extract value from big data.
Course Description
Dive into the world of data science, covering programming, statistics, machine learning algorithms, and model deployment. Learn to build predictive models that extract value from big data.
Learning Outcomes
Ability to manipulate data programmatically|Skills to build and train machine learning models|Competence in evaluating model performance|Proficiency in communicating data science findings
Target Audience
Data analysts|Software developers|Statisticians|Quantitative professionals
8 Modules
0 Lessons
24h 40m
Python programming fundamentals, NumPy arrays, pandas DataFrames, data wrangling techniques, and working with real-world messy datasets.
No lessons in this module yet.
Linear algebra (vectors, matrices), calculus intuition (gradients), probability theory, and statistical distributions that underpin ML algorithms.
No lessons in this module yet.
Systematic EDA methodology, univariate and bivariate analysis, detecting outliers and missing values, feature engineering, and preparing data for modelling.
No lessons in this module yet.
Linear and polynomial regression, evaluation metrics (RMSE, MAE, R²), regularisation (Ridge, Lasso), and building a regression pipeline in Scikit-learn.
No lessons in this module yet.
Logistic regression, decision trees, random forests, and gradient boosting (XGBoost). Classification metrics (accuracy, precision, recall, AUC-ROC).
No lessons in this module yet.
K-Means and hierarchical clustering, dimensionality reduction (PCA, t-SNE), anomaly detection, and practical applications in customer segmentation.
No lessons in this module yet.
Cross-validation, hyperparameter tuning, overfitting and underfitting, and deploying a model as a REST API using Flask or FastAPI.
No lessons in this module yet.
Neural network fundamentals, TensorFlow/Keras basics, and an introduction to text preprocessing and sentiment analysis with NLP techniques.
No lessons in this module yet.
Vocational Training Course
Certificate included
70 hours content
Downloadable resources
Mobile access
Practical skills guarantee
Course Details
Duration
70 hours
Skill Level
Advanced
Learning Method
Self Study
Category
Technology and Data
Modules
8
Total Lessons
0
Last Updated
August 2025