The data science with python course is the second course in the data science learning path. It prepares you for a data analyst or junior data scientist job. It helps you understand the end to end workflow of a data science project. You will learn how to collect, prepare, explore and visualize data, and applying statistical analysis on business data to deliver useful insights. The course is practical by design and offers students the mentorship and learning support to complete an end to end data science project.

Intermediate

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Part-time

Online Live

7 weeks

70 hours

Upcoming Start Date

Oct 17

Registration Deadline:

October 17, 2023

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About the Course

This course is a part of WeCloudData’s Data Science Bootcamp. It teaches you the necessary data wrangling, data analysis, and predictive analytics skills required for data science. The included portfolio project building and mentoring sessions will provide you with the support needed to develop hands-on experience required for job success.

What you will learn

Data Collection
Data Wrangling
Exploratory Data Analysis
Statistical Analysis & Predictive Analytics

Case-based learning with real-life datasets

Digital Analytics with Google Analytics Data
A/B Testing for Product analytics
Social Media Analytics
Customer Analytics

Pre-requisite

To have a positive learning experience and maximal learning outcome, you need to have 2+ months of basic python programming experience.
If you’re new to coding, we highly recommend you take WeCloudData’s Data Fundamentals course or self-paced free Python Course.

Want to learn more about this career?

WeCloudData is the perfect place to grow your career

 5/5

Nhat Tran, Tech Lead, Beamdata

I am reviewing for the two courses I graduated from: Data science with Python and the Data Engineering Bootcamp. This is the best data and AI school available based on my assessment: can you get a job after completing the program? My answer is yes as I have personally found work each time I enrolled in one of their programs – I enrolled in data science and data engineering bootcamps. Importantly, I came for the knowledge, but stayed for the community.

Pros

Teaches you all the relevant topics and skills needed to get the job done in real world
Projects, assignments and exercises to help you build up the muscle memory
Extremely supportive team helping you land a job

Cons

The course and the bootcamp is intense and you will have to provide the focus, effort and time commitment
It will feel overwhelming but it’s worth it in the end

Ranked #1 Data Training Program

 4.9/5

 4.96/5

 4.95/5

CURRICULUM

Be ready for the new economy

WeCloudData Bootcamps are designed to be project-based. We not only cover essential theories, but also teach how to apply tools and platforms that are in high demand today. Our program curriculum is also highly adaptive to the latest market trends.

Module 1

Data Collection

Data collection and extraction is the first step in most of the data science projects. Learners will learn how to extract data from the web and databases using Python in this module. We not only teach students how to code with Jupyter notebooks, but also in the PyCharm or VSCode environment.

LEARNING OUTCOMES

Learn how to extract data from databases using Python and SQL
Learn how to scrape data from the web with Selenium, Scrapy, and Beautifulsoup so learners can build more meaningful and unique portfolio projects
Practice how to extract data from generative AI and LLM APIs for prompt engineering and automation

Key Skill:

Data collection, Web scraping, Web API, Data API

Tools:

Python

VSCode

Jupyter

Scrapy

Tools:

Python

Pandas

spaCy

Module 2

Data Wrangling

Data wrangling is one of the most important skills a data scientist needs to have. Many data science courses tend to focus on statistics and algorithms which give learners the wrong impression about real life data science work. In this module, we will teach students why data manipulation is such a critical skillset and how to wrangle different types of data using Python and Pandas.

LEARNING OUTCOMES

Read and write structured data using Pandas Dataframe
Using Pandas for data transformation tasks such as select, filter, aggregation, merge, and analytics function
Manipulating semi-structured and unstructured data such as xml, json, text, audio, and images
Write reusable data transformation code by following good standards

Key Skill:

Data Wrangling, Data Manipulation, Data Transformation, DataFrame, Text Pre-processing, Window Function

Module 3

Data Analysis

This module teaches the fun part of data science! Students will learn how to explore and visualize data, interpret data using statistics, and analyzing data. Most importantly, learners will learn Python for data analysis under different business contexts such as product analytics, customer analytics, and digital analytics.

LEARNING OUTCOMES

Grasp the general process of data science and analytics
Learn how to explore and visualize data (exploratory data analysis)
Learn basic statistics and apply it for data analysis
Understand different data science use cases such as digital analytics, customer analytics (acquisition, churn, etc.), and product analytics
Learn how to apply statistical testing for data analysis
Learn how to analyze marketing campaigns using AB testing

Key Skill:

Data Visualization, Storytelling, Statistical Analysis, Product Analytics, CRM Analytics, Customer Anaylytics, Digital Analytics, AB Testing

Tools:

Python

Pandas

Matplotlib

Plotly

Tools:

Python

Numpy

Scikit-learn

H2O

Module 4

Predictive Analytics

In this module, learners will get exposed to predictive analytics. We will cover concepts such as regression analysis, time series analysis, and give an introduction to machine learning and autoML. This module will help learners understand the machine learning workflow and how to apply python and autoML tools to create predictive insights.

LEARNING OUTCOMES

Understand the end to end process of machine learning workflow
Understand the different types of ML problems
Learn how to use python to prepare data for predictive analytics
Learn how to use Python and AutoML libraries to create predictive models

Key Skill:

AutoML, Predictive Modeling, Predictive Analytics, Numpy Arrays, Scikit-Learn, Regression Analysis, Time Series Analysis

FACULTY TEAM

Learn from the best

We’ve brought together a team of highly skilled and experienced instructors to help you learn effectively. Our instructors have a passion for teaching and a wealth of real-world experiences in their respective fields, so you can be confident that you’re learning from the best.

Tianshu Luan

Data Science Assistant Instructor @WeCloudData

Tianshu is a Data Science Assistant Instructor at WeCloudData. Prior to joining WeCloudData, Tianshu worked as a high school teacher in Mathematics in various public and private schools in Ontario. Through his teaching career, he is extremely interested in how data collection, data processing, and data analysis can help students in Statistics and help improve the private school system. In his role of Data Science Assistant Instructor, Tianshu is responsible for material and course designing, leading labs, and providing assistance to students. He is very passionate about exploring the possibilities in Python, SQL, and Machine Learning.

Shaohua Zhang

Chief Instructor (WeCloudData) | Head of Data Science (BeamData) | Startup Advisor and Data Coach

Shaohua is the Co-founder and Chief Instructor at WeCloudData. In the past few years, he has trained hundreds of students and helped many of them launch their data science careers. He is also the CEO and Head of Data Science at Beam Data where he works closely with the industry partners on implementing data science projects. Prior to co-founding the Toronto Institute of Data Science and Technology (WeCloudData), he led the data science team at BlackBerry and helped build the data science practice at Kik. He has also worked with big companies such as TD, Canadian Tire, Sunlife, CIBC, Communitech, and MaRS on upskilling their data teams.

Rogelio Cuevas

Director, Data Scientist (Sun Life) | Data Science Instructor (WeCloudData) | Career Mentor (WeCareer)

Rogelio Cuevas currently works as a Director of Data Science in the financial industry in Toronto and as a Data Science mentor for a San Francisco start-up. His educational background has allowed him to work in various research-oriented institutions that include Duke University, McMaster University, University of Western Ontario, and Fermilab. His past research activities made him a recipient of a postdoctoral Fellowship awarded by the Natural Science and Engineering Research Council of Canada.

Project

Portfolio Project Building

Learn how to define the use case and build a data analysis strategy
Develop Python scripts to collect data via web scraping or web APIs
Define data models and load data into databases
Use Python and SQL to clean and analyze data
Prepare data for analytics and insights
Data visualization using Python libraries such as Plotly Dash or Streamlit
Present your project along with the insights to experienced data science experts

SCHEDULE

Upcoming Start Dates

Oct 17 -

Nov 18

Online Live

$3,500.00

Feb 01 -

Mar 02

Online Live

$3,500.00

Explore your personalized learning path

Data Science with Python

$3,500

Build essential skills required for becoming a data scientist
Flexible payment plan
Get this course’s tuition waived when you decide to join the data science bootcamp

Recommended Short Courses

$2,000 - $6,000

Learn advanced skills to stand out
Get alumni discount for the machine learning and big data courses
Short courses to consider after completing this course ⇩

Big Data for Data Scientists

Learn More >

Applied Machine Learning

Learn More >

Upgrade to Bootcamp

$8,000 - $16,000

Upgrade to the part-time DS bootcamp and get $3500 off!
Get extensive 1-1 career mentoring and job support
Get the flexibility to create your own bootcamp

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What our graduates are saying

 5/5

Shelley Geng, Senior Analyst

Excellent experience in Weclouddata! The courses are well-organized and keeping up with the ever-evolving data science trend. Each lecture covers a specific DS topic and theory, followed by a real coding demo session, which is really valuable for a data course. Plus, the assignment for each lecture is fully leveraging what has already been learned and requires students’ efforts to dig deeper — I only wish I would have more time after work to go over all of them.

 5/5

Sinthushan Sooriyakumar, Data Analyst

I started this course without formal programming or statistic/math background. I really enjoyed the top-down approach used by the Instructor, not only does it keep you interested when learning the libraries and syntax, it also drives you to peruse more self-learning. The instructor along with the TA was very approachable and encouraging. I enjoyed showing them where I was in regards to the class projects and getting feedback on what I could try next. The live coding made the class engaging and not only helped show the process that a developer might take when solving a problem. This class was a great experience and I would definitely recommend it to not only those seeking careers in data science but for those who just want a general taste in programming as well.

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FAQ

Frequently asked questions about the bootcamp

Are there pre-requisites for this course?

Yes. We don’t teach python from scratch in this course. So learners will need to know python before attending this course. We highly recommend the Data Fundamentals course as a starter.

How hands-on is the data science course?

The Python for Data Science course is very hands-on by design. Learners will start to work on a capstone project starting from the 2nd week. There’re lots of exercises that will keep learners busy. The lectures are also taught in a hands-on fashion. Learners will follow instructors and TAs to complete labs.

Will I be able to start job searching after taking this course?

Yes, you will have the right skills to apply for data analytics jobs and junior data science jobs. When the job market is very competitive, you will definitely need to learn more in order to stay competitive. But this course will teach you the right data science skills to get started. Other courses we would recommend include machine learning course and big data course.

Are the skills taught in this course in demand?

The data science course teaches you very relevant job skills. A data scientist usually work on data extraction using SQL or Python, data visualization using Python, exploratory data analysis (EDA) using Python, and predictive analytics using machine learning. This course teaches learners how to use Python and the Pandas library to scrape, extract, prepare, visualize, and analyze data. It covers the basics of predictive analytics at the end as well. So in short, you will learn data skills and tools that are highly in demand. However, if you would like to become specialized in machine learning, we would recommend you take the Applied Machine Learning course as well.

What will the learner build in the capstone project?

For the portfolio project, learners will learn how to define the use case and build a data analysis strategy first. Then you will develop Python scripts to collect data via web scraping or web APIs, define data models and load data into databases. After data has been created, learners will learn how to use Python and SQL to clean and analyze data, prepare data for analytics and insights. At the end of the project, learners will present their projects along with the insights to experienced data science experts and get feedback.

Data science is not just about tools. Do you teach practical use cases and how data science is applied in real life?

Yes. This is the key differentiator of WeCloudData’s data science course. We not only teach students tools, but also introduce lots of industry use cases. In fact, we also use some real-life industry datasets for teaching and students will learn how to APPLY data science skills in various business contexts.

How much learning support do I get in the course?

You can communicate with the instructors and teaching assistants (TA’s) regularly through our online platform and communication app (Slack). We host live lab sessions and office hours. On-demand 1-1 support is also available.

What if I miss a few sessions?

The live lectures are all recorded so you will be able to watch them and catch up in case you miss a class. You can also join the office hours to ask questions about the missed lessons.

Do you offer financial support?

Yes. We offer scholarships, flexible payment plans, and student loans via 3rd party lenders. Please fill out the form on the course page to get in touch with our learning advisors.

Will my employer cover the expense for this type of course?

Some students have their employers cover the tuition. You can always ask your employers about it. We’re happy to provide the curriculum and enrolment letter.

WeCloudData is the leading data science and AI academy. Our blended learning courses have helped thousands of learners and many enterprises make successful leaps in their data journeys.

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Data Science

Data Science with Python

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About the Course

WeCloudData is the perfect place to grow your career

Ranked #1 Data Training Program

CURRICULUM

Be ready for the new economy

Key Skill:

Tools:

Tools:

Key Skill:

Key Skill:

Tools:

Tools:

Key Skill:

FACULTY TEAM

Learn from the best

Project

Portfolio Project Building

SCHEDULE

Upcoming Start Dates

Explore your personalized learning path

Data Science with Python

Recommended Short Courses

Big Data for Data Scientists

Applied Machine Learning

Upgrade to Bootcamp

Data Engineering Bootcamp

Data Science Bootcamp (Part-Time)

Machine Learning Engineering Bootcamp

Have Questions?

Start Learning With WeCloudOpen

WeCloudOpen Course

WeCloudOpen Workshop

student success

What our graduates are saying

Let WeCloud Accelerate Your Career in Tech

Have questions?

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View our Data Science with Python course package