TTFA Academy · A fellowship for people at work
For analyst comfortable with SQL and ExcelData Scientist
Python, SQL and Power BI first, then machine learning and the MLOps that gets a model out of the notebook.
Who this is for
You already do part of this job. The program closes the gap between where you are and being seen as a Data Scientist.
Probably not for you, yet
If you haven't worked in the domain at all, a counsellor will say so on the call and point you to a better starting program. If you want a certificate more than a portfolio, this isn't it.
What you'll build
Each project is modelled on the mentors' production work and reviewed 1:1. Together they are your portfolio.
Project 1
Modelled on the mentor's production work, with the messy parts left in, reviewed 1:1.
Project 2
Brief, build, review: the way a manager would hand it to you, with the checks that stop it breaking next month.
Project 3
Published, documented and defended, with the notes a senior would give you.
Curriculum
24 to 36 weeks, depending on your pace. Each module ends with an assignment a mentor reviews.
7 modules · 56 topics · pick a module to see what it covers
Module 1 of 7
Equip learners with strong Python and EDA foundations to analyze, clean, visualize, and prepare data for analytics and machine learning.
Understanding Data Science
Introduction to Data Science lifecycle and industry applications. · Roles in Data Science: Data Analyst, Data Scientist, ML Engineer.
Data Types & Data Sources
Structured vs Unstructured data. · Data sources such as databases, APIs, spreadsheets, and cloud platforms.
Data Science Workflow
Data collection, cleaning, analysis, modeling, and deployment. · Real-world use cases across finance, healthcare, marketing, and e-commerce.
Environment Setup
Installing Python, Jupyter Notebook, and Anaconda. · Introduction to GitHub for version control.
Python Basics
Syntax, keywords, and indentation rules. · Variables, data types, and operators.
Control Flow
Conditional statements (if, elif, else). · Loops (for, while) and iteration techniques.
Functions
Creating reusable functions. · Lambda functions and functional programming.
Python Packages
Introduction to modules and packages. · Installing and managing libraries using pip.
Tools
You use each one on the kind of data your mentors handle at work, not on a toy example.
Learn Python programming for data analysis, data manipulation, and machine learning using libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow.
Develop the ability to extract, manage, and analyze large datasets from relational databases using SQL queries and advanced data operations.
Understand descriptive statistics, probability, and exploratory data analysis (EDA) to identify patterns, trends, and insights in datasets.
Create interactive dashboards and reports using Power BI and Python visualization libraries to present meaningful insights for business decision-making.
Build predictive models using machine learning algorithms, feature engineering, and model evaluation techniques.
Learn neural networks and deep learning frameworks to solve complex problems such as image recognition, NLP, and advanced predictive analytics.
TTFA Academy is an independent training provider. It is not affiliated with, endorsed by or a partner of Microsoft, Salesforce or Alteryx. Microsoft, Power BI, Excel and Fabric are trademarks of the Microsoft group of companies. Tableau is a trademark of Salesforce, Inc. Alteryx is a trademark of Alteryx, Inc. Names are used only to identify the tools taught.
LMS EXPERIENCE
Learn at your pace, practice through real-world projects, build your skills, earn certifications, and discover opportunities that match your potential.
Complete industry-relevant courses designed to build practical skills and prepare you for real-world applications.
Put your learning into practice with assignments and hands-on projects designed to build practical skills and help you grow with confidence.
Practise real-world tasks with interactive simulators that help you apply your knowledge, sharpen your skills, and prepare for the workplace.
Upload and enhance your resume, then discover job and freelance opportunities matched to your skills, experience, and career goals.
Complete projects, build your skills, and unlock certifications at each level as you progress through your learning journey.
Your mentors
Names, employers and photos appear only with their written permission.
Jitendra Singh
Data Science with Python
Jitendra Singh
Lead Instructor
Jitendra leads instruction at TTFA across the analytics stack: Alteryx workflows, Tableau and Power BI dashboards, SQL and Python on real company data, and the GenAI layer on top of them, from agents and MCP to RAG. He teaches the job the way it is done at work: real data, in the order you meet it, with the mistakes left in.
Sarvdeep Singh
Data Science with Python
Sarvdeep Singh
Data & BI mentor
Sarvdeep mentors across the Data & BI programs: Power BI dashboards, SQL for the questions behind them, and Excel for the analysis most teams still start in, with the reporting discipline that makes an analyst's numbers trusted on a Monday morning.
Jayant Yadav
Data Science with Python
Jayant Yadav
Data scientist, Python
Jayant trains Python for analysis and data science as an analyst uses them: cleaning, exploring and explaining data before any model, building and checking the model afterwards, and Microsoft Fabric for the platform underneath.
How the weeks run
A counsellor confirms the exact days and times for your batch on the call.
Two evenings a week with the mentor, on the work of the week.
Project time with the mentor in the room: build, get stuck, get unstuck.
Every class recorded the same day; 1:1 doubt-solving whenever you're stuck.
Your projects reviewed like production work, with notes you can act on.
Data & BI
Programs next to this one. A counsellor will tell you which fits what you do today.
MIS, ops or finance reporting in Excel
Data Analyst
Data or MIS analyst
BI Developer
Analyst doing manual reporting
BI & Automation Consultant
Questions
Anything else: ask on the call.
Yes. The program assumes you know your work, not the tool. If you've never worked in the domain, a counsellor will point you to a better start.
Every class is recorded the same day, and 1:1 slots exist for exactly this. Most people who fall behind catch up in a week.
There is career support: mock interviews, profile reviews and referrals where we have them. Nobody honest can promise you a role; your projects make the case for you.
A counsellor looks at what you do today and tells you, straight, whether Data Science with Python is the right next step.
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