Master the essentials of data science and machine learning with a program designed to transform raw data into actionable insights.
This course provides a strong foundation in data science and machine learning. Learn to analyze complex datasets, extract insights, and build predictive models through practical, hands-on projects in data wrangling, exploratory analysis, and core machine learning techniques.
This foundation course blends theory with hands-on practice, guiding learners through the complete data workflow from preprocessing and visualization to building and interpreting predictive models.
This course is ideal for aspiring data analysts, engineers, and professionals seeking to build a strong foundation in data science and machine learning without requiring prior advanced experience in programming or statistics.
The following courses or modules are included in this program. Course content and structure may vary slightly by cohort.
Learn how to handle, clean, and prepare raw datasets for analysis using Python and industry-standard libraries.
Develop the ability to uncover patterns, trends, and relationships in your data through visualization and statistical techniques.
Gain a practical understanding of supervised and unsupervised learning algorithms, including model training and evaluation.
Learn to assess model performance and interpret results for actionable decision-making.
Create compelling visual narratives to communicate data insights effectively using tools like Matplotlib and Seaborn.
Build proficiency in Python programming tailored for data manipulation, analysis, and machine learning tasks.
The program is divided into carefully sequenced modules covering data preparation, analysis, visualization, and machine learning. Each module combines conceptual lectures with practical exercises and culminates in a hands-on project to reinforce real-world application.
The following courses or modules are included in this program. Course content and structure may vary slightly by cohort.
Master the fundamentals of data exploration, cleaning, and interpretation to gain insights and prepare for advanced data science and machine learning tasks.
Learn to organize, clean, and analyze data using Excel tools, formulas, and visualizations to uncover insights for data-driven decisions.
Learn to query, clean, and analyze datasets using SQL to uncover insights and support data-driven decisions.
Learn to present data effectively using charts, graphs, and dashboards to uncover insights and patterns.
Learn to collect, analyze, and visualize data to support informed decision-making and gain actionable insights.
This program runs in fixed cohorts with limited seats to ensure focused instruction and effective learning.
Tue
May 2026
This cohort is structured to provide an in-depth understanding of both the theoretical foundations and practical applications of data science and machine learning.
Tue
Sep 2026
This cohort is structured to provide an in-depth understanding of both the theoretical foundations and practical applications of data science and machine learning.
Delivered through an interactive, online platform, the course offers a blend of video lectures, guided tutorials, quizzes, and project-based assignments to ensure an engaging and flexible learning experience.
Upon successful completion of the course and final project, learners will receive a recognized certificate, validating their skills in data science and machine learning foundations.
Participants are expected to have basic computer literacy and an interest in data-driven problem-solving. No prior experience in coding or machine learning is mandatory, though familiarity with basic mathematics is beneficial.
Explore available programs and upcoming cohorts to see how NovelTech Academy can support your learning goals.
