Data Science Career Path: 100 Days of Data Science Bootcamp

A Structured 100-Day Roadmap to Become a Job-Ready Data Scientist

 Course Overview

Data Science Career Path: 100 Days of Data Science Bootcamp is a carefully designed, long-term learning program built for learners who want clarity, structure, and real progress in data science.

Instead of scattered lessons or theory-heavy explanations, this bootcamp follows a daily learning model. Each stage builds logically on the previous one, helping learners develop strong foundations first, then move confidently into machine learning and deep learning.

This course focuses on understanding, practice, and consistency, making it suitable even for complete beginners who are serious about building a career in data science.

Quick Course Facts

• Instructor: Shahriar’s Analytical Academy
• Level: Beginner to Intermediate
• Language: English
• Total Duration: ~48.5 Hours
• Students Enrolled: 3,900+
• Rating: ⭐ 4.9 / 5 (Highest Rated)
• Certificate: ✅ Yes
• Access: Lifetime (Mobile & TV)

Data Science & Machine Learning(Theory+Projects)A-Z 90 HOURS

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Data Science & AI Masters 2025 – From Python To Gen AI

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 What You Will Learn (Simplified)

Data Science Foundations

• What data science is and how it’s used in real industries
• How data scientists approach and solve problems
• Understanding the full data science workflow

Python for Data Analysis

• Python basics for absolute beginners
• Working with variables, loops, functions, and OOP
• Data handling using pandas and NumPy

Data Cleaning & Exploratory Analysis

• Cleaning messy real-world datasets
• Handling missing values and outliers
• Exploring data patterns and relationships
• Practical EDA using pandas and visualization libraries

Data Visualization

• Creating meaningful charts and plots
• Interpreting trends using visual insights
• Communicating findings clearly with data

Statistics & Probability

• Descriptive and inferential statistics
• Hypothesis testing and confidence intervals
• Understanding data uncertainty and variation

Essential Mathematics for Data Science

• Linear algebra basics for ML intuition
• Core calculus concepts behind optimization
• Understanding how models learn

 Machine Learning

• Regression, classification, and clustering models
• Model training, validation, and evaluation
• Bias vs variance, overfitting, and performance metrics

 Advanced ML Techniques

• Feature engineering and preprocessing
• Cross-validation and hyperparameter tuning
• Ensemble models (Random Forest, XGBoost, LightGBM, etc.)

Deep Learning Introduction

• Neural network fundamentals
• Building and evaluating models with TensorFlow
• Understanding how deep learning works conceptually

Hands-On Learning & Projects

• Real-world datasets (not toy examples)
• Daily coding exercises for skill reinforcement
• Assignments designed to build portfolio confidence
• End-to-end project workflows similar to industry tasks

 Who This Course Is For

• Absolute beginners in data science
• Learners confused by scattered online resources
• Students seeking a clear daily learning plan
• Career switchers aiming for analytics or ML roles
• Anyone serious about building long-term data skills

 Why the “100 Days” Format Works

• Encourages daily learning habits

• Prevents overload and burnout

• Builds skills gradually and logically

• Reinforces concepts through repetition and practice

• Helps learners stay consistent and accountable

 One Honest Limitation

This course emphasizes code, explanation, and thinking, not flashy animations.
It’s ideal for learners who prefer depth and clarity over entertainment-style videos.

 Final Verdict

If you’re looking for a serious, structured, beginner-friendly path into data science, this bootcamp stands out for its clarity, depth, and discipline-focused approach.

It’s not a shortcut — but it is a reliable roadmap for learners who want real skills, real understanding, and real career readiness.