Global Certificate in Data Science Essentials: Analytical Techniques

-- viewing now

The Global Certificate in Data Science Essentials: Analytical Techniques is a comprehensive course that imparts critical data science skills in high demand by today's industries. This program equips learners with essential knowledge in data manipulation, visualization, and analytical techniques using real-world data, empowering them to derive valuable insights and make data-driven decisions.

4.5
Based on 3,471 reviews

3,476+

Students enrolled

GBP £ 140

GBP £ 202

Save 44% with our special offer

Start Now

About this course

By blending theoretical understanding and practical application, this course covers fundamental concepts such as probability, statistical inference, and regression analysis. Learners will gain hands-on experience with powerful tools like Python, pandas, NumPy, and matplotlib, ensuring they are well-prepared to tackle various data science challenges. In an era driven by data, this certification course is a stepping stone to numerous high-growth careers, including Data Analyst, Data Scientist, Business Intelligence Analyst, and Business Analyst. Successfully completing this program will not only enhance learners' analytical skills but also provide a strong foundation for further studies in advanced data science methodologies. Invest in your future by gaining the essential skills needed for career advancement in the rapidly evolving field of data science.

100% online

Learn from anywhere

Shareable certificate

Add to your LinkedIn profile

2 months to complete

at 2-3 hours a week

Start anytime

No waiting period

Course Details

Data Collection Techniques: An introduction to various data collection methods, including surveys, web scraping, interviews, and experiments. Emphasis on selecting the appropriate method based on the research question and data type.
Data Cleaning and Pre-processing: Techniques for cleaning and preparing datasets for analysis, such as handling missing values, outliers, and inconsistent data.
Data Visualization: An overview of data visualization techniques, including chart types, color theory, and best practices for creating effective visualizations.
Exploratory Data Analysis: Methods for exploring and summarizing datasets, including measures of central tendency, variability, and correlation.
Statistical Inference: Foundational concepts of statistical inference, including hypothesis testing, confidence intervals, and p-values.
Regression Analysis: Techniques for modeling relationships between variables using linear and logistic regression. Includes an introduction to assumptions, diagnostics, and model selection.
Machine Learning Fundamentals: Overview of machine learning approaches, including supervised, unsupervised, and reinforcement learning.
Experimental Design and Causal Inference: Methods for designing experiments to test causal relationships, including randomized controlled trials and natural experiments.
Ethics in Data Science: Discussion of ethical considerations in data science, including privacy, bias, and fairness in algorithmic decision-making.

Career Path

The Global Certificate in Data Science Essentials: Analytical Techniques program prepares professionals for diverse roles in the UK's growing data science job market. This 3D pie chart highlights the distribution of opportunities in various roles, including Data Scientist, Data Analyst, Data Engineer, Data Administrator, and Business Intelligence Developer. The demand for data science skills varies across industries, with Data Scientists leading the pack at 35%, followed by Data Analysts at 25%. Data Engineers comprise 20% of the market, while Data Administrators and Business Intelligence Developers each hold 15% and 5%, respectively. With the UK's increasing focus on data-driven decision-making, these roles will remain in high demand. This responsive 3D pie chart, with a transparent background and no added background color, adapts to all screen sizes, making it an engaging visual representation of the evolving UK job market trends in data science essentials.

Entry Requirements

  • Basic understanding of the subject matter
  • Proficiency in English language
  • Computer and internet access
  • Basic computer skills
  • Dedication to complete the course

No prior formal qualifications required. Course designed for accessibility.

Course Status

This course provides practical knowledge and skills for professional development. It is:

  • Not accredited by a recognized body
  • Not regulated by an authorized institution
  • Complementary to formal qualifications

You'll receive a certificate of completion upon successfully finishing the course.

Why people choose us for their career

Loading reviews...

Frequently Asked Questions

What makes this course unique compared to others?

How long does it take to complete the course?

What support will I receive during the course?

Is the certificate recognized internationally?

What career opportunities will this course open up?

When can I start the course?

What is the course format and learning approach?

Course fee

MOST POPULAR
Fast Track: GBP £140
Complete in 1 month
Accelerated Learning Path
  • 3-4 hours per week
  • Early certificate delivery
  • Open enrollment - start anytime
Start Now
Standard Mode: GBP £90
Complete in 2 months
Flexible Learning Pace
  • 2-3 hours per week
  • Regular certificate delivery
  • Open enrollment - start anytime
Start Now
What's included in both plans:
  • Full course access
  • Digital certificate
  • Course materials
All-Inclusive Pricing • No hidden fees or additional costs

Get course information

We'll send you detailed course information

Pay as a company

Request an invoice for your company to pay for this course.

Pay by Invoice

Earn a career certificate

Sample Certificate Background
GLOBAL CERTIFICATE IN DATA SCIENCE ESSENTIALS: ANALYTICAL TECHNIQUES
is awarded to
Learner Name
who has completed a programme at
London College of Foreign Trade (LCFT)
Awarded on
05 May 2025
Blockchain Id: s-1-a-2-m-3-p-4-l-5-e
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
SSB Logo

4.8
New Enrollment