AllWomen

Data Analytics Foundations On Demand Course

Learn the main concepts and skills needed to analyze statistics, prepare data sets, summarize data, and create data visualizations.

Overview

Curious about the field of Data Analytics?

With our Data Analytics Foundations On Demand Course, you will be exposed to real examples of how top companies build products that people love while learning the tools and skills needed for it.

Course Computer Icon

25 hours course

Course Calendar

Self - paced with optional live sessions

Course Books

Hands-on experience

Course Pencil

Multi-format content approach

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Mentoring

Course Hands

allWomen Community

Course Computer Icon

25 hours course

Course Calendar

Self - paced with optional live sessions

Course Books

Hands-on experience

Course Pencil

Multi-format coontent approach

Course Handshake

Mentoring

Course Hands

allWomen Community

Self - paced learning

We know you are busy, so the course is designed to go at your own pace. Once you sign up, the whole content of the course is released in our online learning platform where you will be able not only to do the course but also to connect with other women in tech and with a team of Data Analysis experts and mentors that will be present to guide discussions, host monthly live sessions with real case industry case studies, provide career advice, support and feedback and foster peer connection.

Along the course, you have the opportunity to complete an optional final project that will help you build your portfolio as Data Analyst. If you'd like to do this final project, you should count with 8 additional hours of work.

You will have one whole year access to the course but you'll need to do it in 3 months if you want to obtain a certificate.

Download the syllabus to learn more about the course.

with optional monthly live sessions and final project

Course Outcomes

Hard and Soft Skills of a Data Analyst that you will develop in this course:

Hard Skills you will develop:

Soft Skills you will develop:

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Creativity

Skepticism

Collaboration

04 Public Speaking

Public Speaking

What our AW alumna say

Giovanna Jaramillo
allWomen Alumna
Epistemologist & Data Expert

"allWomen has had a profound impact on my personal journey transitioning into tech by giving me a vibrant and exciting space to learn and by exposing me to terrific women leaders working in Data."

Lead Instructor

Learn from female industry experts

Jovana Urosevic
Lead Instructor
Computational Linguist at LinkedIn

Jovana is a Computational Linguist working at Linkedin where she uses natural language processing (NLP), data analysis, and general linguistic expertise to help improve and optimize language understanding of AI products.

Jovana holds a masters degree in NLP and her passion is to contribute to the development of technology for the different languages she speaks as well as being the “human in the loop”, bridging the gap between human-generated content and machine learning algorithms.Jovana joined allWomen as a Data Science/Data Analytics instructor in 2020 and has since helped many of our students to acquire new knowledge of programming, analytics, machine learning and to set them up for a successful career progression within the data space.

Multi-format content approach

Never get bored!

Our course is designed with your motivation in mind, let’s do this girl!


📹 10 to 15 videos per course.
🎧 5 podcasts with industry guests.
✍️ 5 to 10 hands-on exercises.
🗒 5 assessments to self evaluation.
🙋‍♀️ Slack workspace with Mentor support & office hours.


🤝 Optional monthly live online sessions with tech companies case studies and career coaching workshops.
👩‍💻Optional final project to put all your new skills into practice.
🏅Certificate upon completion within 3 months after sign up to the course.

Our Instructors, Mentors and Alumna work at

Tuition Fee

Sign up now at the best price!

Regular Fee: 499€

449€

With the code: DATALAUNCH 💸

Referral Program:

For each friend you bring we'll reimburse you 50€ 💸

Who is this for

Looking to learn something new or boost your career?

If you're hoping to become a Data Analyst or to dive deeper into the subject, there is no singular background or path to do it but some of our alumna are...

Discoverers: Women without a data analytics background who are driven and passionate about the data field and want to take a step into the tech sector.

Upskillers: Women who are established in their professional career and want to take it to the next level by adding Data Analytics skills to their resume

Data users: Women who want to take one step further and combine their data knowledge with modern and advanced techniques to level up.

Course Structure and Learning Objectives

Course Structure - 25 hours:

Module 1

Introduction to Data Analytics

  • Understand common processes and key analytical skills used by data analysts in their day-to-day (which you will develop throughout this course); 
  • Understand the data life-cycle and the common data analysis processes.
Module 2

Data wrangling with Python

  • Know Pandas fundamental.
  • Know how to prepare your data for analysis and run basic statistics.
Module 3

Exploratory Data Analysis

  • Understand what EDA is and why we need it.
  • Know how to apply EDA to a real-world example using the Pandas library. To understand the full EDA process, this unit is further complemented with Descriptive Statistics and Visualizations units in order to fully equip you to independently implement EDA on any dataset.
Module 4

Descriptive Statistics

  • Know how to describe data from various dimensions: central tendency, dispersion, shape of the data
  • Understand what univariate analysis is and how to implement it
  •  Understand what bivariate analysis is and how to implement it.
Module 5

Visualization and Storytelling

  • Understand the importance of data visualization;
  • Know how to use Plotly in Python to create powerful visualizations;
  • Know how to effectively present and communicate your insights through data storytelling.

Download the Data Analytics Foundations On Demand Course syllabus for a comprehensive overview of the course.