Data Science

Course Description

Learn the tools to become a Data Scientist with hands-on training and mentoring from industry experts. Analyze data with Python, create machine learning models and interactive visualizations, and query databases with SQL PRE-COURSE REQUIREMENTS & TARGET GROUP Trainees within age group 18 years and above that possesses a SSCE Certification. All Participants are required to have a personal laptop. COURSE DURATION The course is 8 weeks | 3 days a week: (9:00am – 5:00pm) HOSTEL ACCOMODATION This is available at an extra cost MODE OF DELIVERY •Classroom Presentation - using PowerPoint and visual aids •practical sessions, audio/video resources •One-to-one instruction and team-building exercises in groups. Feedback from the participants during each topic forms an important element of the learning process. LEARNING OBJECTIVES On successful completion of this course each trainee will have a comprehensive understanding of the following: •Describe what data science is used for •List the stages in the data science process •Understand database structure •Explain what machine learning is and the parts that make it up •Discuss the use of regression and the different types of regression •Identify the different types of classification algorithms available •Python programming alongside jupyter, notebook, google colab, data wrangling, visuals and pandas for analysis. •The concept of statistics and its relationship with probability. •Live data and predictions, build visualization •Data modeling and building dashboard COURSE CONTENT/TOPIC •Introduction to data science •What is Data and database with types •Database table and structure •Data science process and statistics •Data science methodologies •Machine learning •Regression •Classification •Clustering •Data science technologies •Python for data science •Python programming and google colab •Python operators and conditional operators •Python tuples and function •Statistic and probability •Statistic for data science •Probability and hypothesis testing •Numpy data analysis •Loan prediction analysis •Wine quality prediction •Deep learning with keras and tensor flow •Breast cancer classification •Sentiment analysis •Computer vision with pytorch and open Cv ASSESSMENT • Multiple-choice examination & Project based practical examination CERTIFICATE On completion learners will receive Etiwa Tech Certificate

Contact Details

• ETIWA TECH

  ETIWA TECH, Lagos, Nigeria

  +234 814 436 0692

  info@etiwatech.org