Structured study plan

MLS-C01 60-Day Study Plan

Pass AWS Machine Learning Specialty in 60 days with 1.5 hours of daily study. This plan follows the official blueprint weights so you spend the most time where the exam spends the most marks. 2,228 practice questions available.

30 Days 60 Days 90 Days

Total days

Study weeks

1.5

Hours/day

2,228

Practice questions

Domain Allocation

Days assigned by official exam weight

Exploratory Data Analysis24% of exam
60 days~9 Q/dayPractice →

Week-by-Week Schedule

Week 1— Exploratory Data Analysis

7 days

Exploratory Data Analysis
Exploratory Data Analysis is 24% of MLS-C01 and covers preparing and understanding data before modelling. The exam tests your ability to choose the right AWS tool for the job: Athena and Glue for querying and cataloging S3 data, SageMaker Data Wrangler and Ground Truth for transformation and labeling, and statistics such as correlation, class imbalance, and outliers.
📅 Days 1–7🎯 ~9 questions/day⚖ 24% of exam
Study →
- ✓Query S3 data with Amazon Athena and catalog schemas using AWS Glue Crawlers
- ✓Build visual transformations and detect anomalies with SageMaker Data Wrangler
- ✓Compute summary statistics and correlations using pandas, NumPy, and SageMaker notebooks

Week 2— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 8–14🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 3— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 15–21🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 4— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 22–28🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 5— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 29–35🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 6— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 36–42🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 7— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 43–49🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 8— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 50–56🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 9— Exploratory Data Analysis

4 days

(continued)Exploratory Data Analysis
📅 Days 57–60🎯 ~9 questions/day⚖ 24% of exam
Study →

How to use this 60-day plan

→Commit to 1.5 hours per day — consistency beats marathon sessions.
→Start each domain by reading the objective description, then immediately move to practice questions.
→Don't skip domains with low weight — exam questions can come from any domain.
→When you finish a domain, score ≥ 80% on its practice questions before moving on.
→In the final 3 days, do full mixed-domain practice tests to simulate real exam conditions.
→Review wrong answers immediately — understanding why you were wrong is more valuable than getting it right.

Other study plan lengths

30-Day Plan 90-Day Plan Start Practice Test →

Structured study plan

MLS-C01 60-Day Study Plan

30 Days 60 Days 90 Days

Total days

Study weeks

1.5

Hours/day

2,228

Practice questions

Domain Allocation

Days assigned by official exam weight

Exploratory Data Analysis24% of exam
60 days~9 Q/dayPractice →

Week-by-Week Schedule

Week 1— Exploratory Data Analysis

7 days

Exploratory Data Analysis
Exploratory Data Analysis is 24% of MLS-C01 and covers preparing and understanding data before modelling. The exam tests your ability to choose the right AWS tool for the job: Athena and Glue for querying and cataloging S3 data, SageMaker Data Wrangler and Ground Truth for transformation and labeling, and statistics such as correlation, class imbalance, and outliers.
📅 Days 1–7🎯 ~9 questions/day⚖ 24% of exam
Study →
- ✓Query S3 data with Amazon Athena and catalog schemas using AWS Glue Crawlers
- ✓Build visual transformations and detect anomalies with SageMaker Data Wrangler
- ✓Compute summary statistics and correlations using pandas, NumPy, and SageMaker notebooks

Week 2— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 8–14🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 3— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 15–21🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 4— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 22–28🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 5— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 29–35🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 6— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 36–42🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 7— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 43–49🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 8— Exploratory Data Analysis

7 days

(continued)Exploratory Data Analysis
📅 Days 50–56🎯 ~9 questions/day⚖ 24% of exam
Study →

Week 9— Exploratory Data Analysis

4 days

(continued)Exploratory Data Analysis
📅 Days 57–60🎯 ~9 questions/day⚖ 24% of exam
Study →

How to use this 60-day plan

→Commit to 1.5 hours per day — consistency beats marathon sessions.
→Start each domain by reading the objective description, then immediately move to practice questions.
→Don't skip domains with low weight — exam questions can come from any domain.
→When you finish a domain, score ≥ 80% on its practice questions before moving on.
→In the final 3 days, do full mixed-domain practice tests to simulate real exam conditions.
→Review wrong answers immediately — understanding why you were wrong is more valuable than getting it right.

Other study plan lengths

30-Day Plan 90-Day Plan Start Practice Test →