How to Cultivate Unbreakable Data Science Habits with Ease
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Chapter 1: The Role of Motivation in Habit Formation
Motivation often serves as the greatest adversary in the journey of habit formation. It's not a lack of motivation that poses a challenge but rather an abundance of it at the onset. New habits are typically sparked by inspiration—whether from a person or an event—that propels you to engage in complex tasks, such as mastering advanced Python or tackling intricate projects. However, this initial enthusiasm tends to wane, leaving you relying solely on self-discipline to sustain these new behaviors.
As self-discipline lacks the fervor that motivation provides, it quickly conjures up countless reasons to retreat to the comfort of distractions like binge-watching your favorite shows. Habits initiated by temporary motivation are set up for failure.
Section 1.1: The Misconception of Progress
Many of us harbor misconceptions about what constitutes "progress." In a world inundated with distractions from social media to entertainment platforms, attempting to embark on new habits with a cold turkey approach is often unrealistic.
Consider this: can you genuinely envision maintaining three new habits for an hour daily over several months? The reality is that few can last even five days under such pressure. Hence, it's essential to redefine your understanding of progress. True progress is not measured by the hours dedicated but by the consistency of your streak.
Subsection 1.1.1: The Power of Small Steps
After years of failing to meet my New Year's resolutions, I discovered that starting small is the most effective way to establish a habit streak. While the advice to "start small" is common, it's often misunderstood. Instead of half an hour or an hour, aim for just five minutes a day.
At first, it was challenging to ignore the voice of motivation urging me to do more. Yet, I knew that sustaining higher intensity would be unsustainable. Surprisingly, by sticking to my five-minute routine, I maintained a nearly 90-day streak, something I had never achieved before.
My strategy involved starting with five minutes daily and then gradually increasing my time by 2.5 minutes each week. Remarkably, within 12 weeks, I had built up to a 30-minute daily commitment for most of my habits.
Section 1.2: A Strategic Approach to Self-Discipline
When faced with an unpleasant task, self-discipline often feels like it's being asked to perform a daunting challenge daily. Consequently, it tends to search for excuses to avoid the task or suggest less taxing alternatives.
By setting a timer for just five minutes, you create a psychological escape route. The task feels manageable, allowing you to trick your self-discipline into spending hours on it without protest.
Momentum builds once you hit a week-long streak across multiple habits. This momentum is unique; it fosters motivation instead of draining it. To keep yourself accountable, utilizing a habit tracker is invaluable.
Chapter 2: Harnessing Momentum and Setting the Rules
In the video "Here's Your DIY Data Science Roadmap!", discover how to effectively structure your learning journey in data science.
In the video "Decision Tree Machine Learning: Stop #1 on Your DIY Data Science Roadmap," learn the fundamentals of decision trees in machine learning.
The Rules for Successful Habit Formation
To achieve lasting change, adhere to these essential rules:
- You can afford to miss a day, but never miss two consecutive days.
- On tough days, aim to complete at least 20% of your daily goal to maintain your streak.
- Always complete the last day of the week, as it sets the stage for your next increment.
Building a New Identity
Finally, embrace a new identity linked to your habits. For instance, label yourself as a data scientist from the moment you start learning. This mindset shift makes it easier to engage in daily tasks associated with that identity.
Choosing Your Data Science Habits Wisely
As you become adept at building habits, you may feel inspired to tackle numerous pursuits. However, be discerning when selecting new habits. Consider whether you genuinely want to learn a particular skill or framework.
Focus on a specific discipline within data science, such as data analysis or machine learning, and build interrelated habits that contribute to your growth as a well-rounded professional. With patience, you'll notice transformative effects on your life within a few months.